Genetic polymorphisms associated with psoriasis, methods of detection and uses thereof

ABSTRACT

The present invention is based on the discovery of genetic polymorphisms that are associated with psoriasis and related pathologies. In particular, the present invention relates to nucleic acid molecules containing the polymorphisms, including groups of nucleic acid molecules that may be used as a signature marker set, such as a haplotype, a diplotype, variant proteins encoded by such nucleic acid molecules, reagents for detecting the polymorphic nucleic acid molecules and proteins, and methods of using the nucleic acid and proteins as well as methods of using reagents for their detection.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a divisional application of U.S. non-provisionalapplication Ser. No. 16/149,492, filed on Oct. 2, 2018, which is acontinuation of U.S. non-provisional application Ser. No. 14/963,923,filed on Dec. 9, 2015 (issued as U.S. Pat. No. 10,131,949 on Nov. 20,2018), which is a continuation of U.S. non-provisional application Ser.No. 13/657,215, filed on Oct. 22, 2012, which is a continuationapplication of U.S. non-provisional application Ser. No. 13/080,458,filed on Apr. 5, 2011, which is a divisional application of U.S.non-provisional application Ser. No. 12/325,832, filed on Dec. 1, 2008(issued as U.S. Pat. No. 7,947,451 on May 24, 2011), which claimspriority to U.S. provisional application Ser. No. 61/005,018, filed onNov. 30, 2007, the contents of each of which are hereby incorporated byreference in their entirety into this application.

FIELD OF THE INVENTION

The present invention is in the field of diagnosis and therapy ofpsoriasis. In particular, the present invention relates to specificsingle nucleotide polymorphisms (SNPs) in the human genome, and theirassociation with psoriasis and related pathologies. Based on differencesin allele frequencies in the psoriasis patient population relative tonormal individuals, the naturally-occurring SNPs disclosed herein can beused as targets for the design of diagnostic reagents and thedevelopment of therapeutic agents, as well as for disease associationand linkage analysis. In particular, the SNPs of the present inventionare useful for identifying an individual who is at an increased ordecreased risk of developing psoriasis and for early detection of thedisease, for providing clinically important information for theprevention and/or treatment of psoriasis, and for screening andselecting therapeutic agents. The SNPs disclosed herein are also usefulfor human identification applications. Methods, assays, kits, andreagents for detecting the presence of these polymorphisms and theirencoded products are provided.

BACKGROUND OF THE INVENTION

Psoriasis is a common, chronic, T-cell-mediated inflammatory disease ofthe skin affecting ˜2-3% of whites of European descent. Although thisdisease is found in all populations, its prevalence is lower in Asiansand African-Americans and also declines at lower latitudes. The mostcommon form, psoriasis vulgaris, is characterized by varying numbers ofred, raised, scaly skin patches that can be present on any body surface,but most often appear on the elbows, knees and scalp. The onset ofdisease usually occurs early in life (15-30 years) and affects males andfemales equally. Up to 30% of individuals with psoriasis will develop aninflammatory arthritis, which can affect the peripheral joints of thehands and feet, large joints, or the central axial-skeleton.Pathologically, psoriasis is characterized by vascular changes,hyperproliferation of keratinocytes, altered epidermal differentiationand inflammation. In particular, the reaction of cells in the epidermisto type 1 effector molecules produced by T-cells results in thecharacteristic pathology of the plaques.

The genetics of psoriasis are complex and highly heritable as evidencedby an increased rate of concordance in monozygotic twins over dizygotictwins (35%-72% vs. 12-23%) and a substantially increased incidence infamily members of affected individuals (first-degree relatives 6%);however, it is clear that environmental effects are also responsible fordisease susceptibility. Ten genome-wide linkage scans have resulted instrong evidence for a susceptibility locus in the MHC region on 6p21(PSORS1 [MIM 177900]), but have not yielded consistent evidence forother regions.

Linkage and association in the MHC (6p21) are thought to be due toHLA-C, in particular psoriasis susceptibility effects are thought to becaused by the *0602 allele, although other candidate genes in the areamay also contribute to disease predisposition. Association studies haveidentified three genes under linkage peaks, with considerable evidencefor linkage disequilibrium with psoriasis, namely SLC9A3R1/NAT9 andRAPTOR (KIAA1303) in 17q25, and SLC12A8 in 3q21. Several other genesincluding VDR, MMP2, IL10, IL1RN, IL12B, and IRF2 (Genetic AssociationDatabase, OMIM) have been associated with psoriasis in sample sets ofvarying sizes and of different ethnicities; however, without more datafrom additional independent studies, it is difficult to drawstatistically sound conclusions about whether these markers are trulyassociated with disease. Thus, there remains a need for the discovery ofreliable markers that can associate themselves with psoriasis, and inturn, would facilitate the diagnosis and treatment of the disease.

The discovery of genetic markers which are useful in identifyingpsoriasis individuals who are at increased risk for developing psoriasismay lead to, for example, better therapeutic strategies, economicmodels, and health care policy decisions.

SNPs

The genomes of all organisms undergo spontaneous mutation in the courseof their continuing evolution, generating variant forms of progenitorgenetic sequences (Gusella, Ann. Rev. Biochem. 55, 831-854 (1986)). Avariant form may confer an evolutionary advantage or disadvantagerelative to a progenitor form or may be neutral. In some instances, avariant form confers an evolutionary advantage to the species and iseventually incorporated into the DNA of many or most members of thespecies and effectively becomes the progenitor form. Additionally, theeffects of a variant form may be both beneficial and detrimental,depending on the circumstances. For example, a heterozygous sickle cellmutation confers resistance to malaria, but a homozygous sickle cellmutation is usually lethal. In many cases, both progenitor and variantforms survive and co-exist in a species population. The coexistence ofmultiple forms of a genetic sequence gives rise to geneticpolymorphisms, including SNPs.

Approximately 90% of all polymorphisms in the human genome are SNPs.SNPs are single base positions in DNA at which different alleles, oralternative nucleotides, exist in a population. The SNP position(interchangeably referred to herein as SNP, SNP site, SNP locus, SNPmarker, or marker) is usually preceded by and followed by highlyconserved sequences of the allele (e.g., sequences that vary in lessthan 1/100 or 1/1000 members of the populations). An individual may behomozygous or heterozygous for an allele at each SNP position. A SNPcan, in some instances, be referred to as a “cSNP” to denote that thenucleotide sequence containing the SNP is an amino acid coding sequence.

A SNP may arise from a substitution of one nucleotide for another at thepolymorphic site. Substitutions can be transitions or transversions. Atransition is the replacement of one purine nucleotide by another purinenucleotide, or one pyrimidine by another pyrimidine. A transversion isthe replacement of a purine by a pyrimidine, or vice versa. A SNP mayalso be a single base insertion or deletion variant referred to as an“indel” (Weber et al., “Human diallelic insertion/deletionpolymorphisms”, Am J Hum Genet 2002 October; 71(4):855-82).

A synonymous codon change, or silent mutation/SNP (terms such as “SNP”,“polymorphism”, “mutation”, “mutant”, “variation”, and “variant” areused herein interchangeably), is one that does not result in a change ofamino acid due to the degeneracy of the genetic code. A substitutionthat changes a codon coding for one amino acid to a codon coding for adifferent amino acid (i.e., a non-synonymous codon change) is referredto as a missense mutation. A nonsense mutation results in a type ofnon-synonymous codon change in which a stop codon is formed, therebyleading to premature termination of a polypeptide chain and a truncatedprotein. A read-through mutation is another type of non-synonymous codonchange that causes the destruction of a stop codon, thereby resulting inan extended polypeptide product. While SNPs can be bi-, tri-, ortetra-allelic, the vast majority of the SNPs are bi-allelic, and arethus often referred to as “bi-allelic markers”, or “di-allelic markers”.

As used herein, references to SNPs and SNP genotypes include individualSNPs and/or haplotypes, which are groups of SNPs that are generallyinherited together. Haplotypes can have stronger correlations withdiseases or other phenotypic effects compared with individual SNPs, andtherefore may provide increased diagnostic accuracy in some cases(Stephens et al. Science 293, 489-493, 20 Jul. 2001). As used herein,the term “haplotype” refers to a set of two or more alleles on a singlechromosome. The term “diplotype” refers to a combination of twohaplotypes that a diploid individual carries. The term “doublediplotype”, also called “two-locus diplotype”, refers to a combinationof diplotypes at two distinct loci for an individual.

Causative SNPs are those SNPs that produce alterations in geneexpression or in the expression, structure, and/or function of a geneproduct, and therefore are most predictive of a possible clinicalphenotype. One such class includes SNPs falling within regions of genesencoding a polypeptide product, i.e. cSNPs. These SNPs may result in analteration of the amino acid sequence of the polypeptide product (i.e.,non-synonymous codon changes) and give rise to the expression of adefective or other variant protein. Furthermore, in the case of nonsensemutations, a SNP may lead to premature termination of a polypeptideproduct. Such variant products can result in a pathological condition,e.g., genetic disease. Examples of genes in which a SNP within a codingsequence causes a genetic disease include sickle cell anemia and cysticfibrosis.

Causative SNPs do not necessarily have to occur in coding regions;causative SNPs can occur in, for example, any genetic region that canultimately affect the expression, structure, and/or activity of theprotein encoded by a nucleic acid. Such genetic regions include, forexample, those involved in transcription, such as SNPs in transcriptionfactor binding domains, SNPs in promoter regions, in areas involved intranscript processing, such as SNPs at intron-exon boundaries that maycause defective splicing, or SNPs in mRNA processing signal sequencessuch as polyadenylation signal regions. Some SNPs that are not causativeSNPs nevertheless are in close association with, and therefore segregatewith, a disease-causing sequence. In this situation, the presence of aSNP correlates with the presence of, or predisposition to, or anincreased risk in developing the disease. These SNPs, although notcausative, are nonetheless also useful for diagnostics, diseasepredisposition screening, and other uses.

An association study of a SNP and a specific disorder involvesdetermining the presence or frequency of the SNP allele in biologicalsamples from individuals with the disorder of interest, such aspsoriasis and related pathologies and comparing the information to thatof controls (i.e., individuals who do not have the disorder; controlsmay be also referred to as “healthy” or “normal” individuals) who arepreferably of similar age and race. The appropriate selection ofpatients and controls is important to the success of SNP associationstudies. Therefore, a pool of individuals with well-characterizedphenotypes is extremely desirable.

A SNP may be screened in diseased tissue samples or any biologicalsample obtained from a diseased individual, and compared to controlsamples, and selected for its increased (or decreased) occurrence in aspecific pathological condition, such as pathologies related topsoriasis, increased or decreased risk of developing psoriasis. Once astatistically significant association is established between one or moreSNP(s) and a pathological condition (or other phenotype) of interest,then the region around the SNP can optionally be thoroughly screened toidentify the causative genetic locus/sequence(s) (e.g., causativeSNP/mutation, gene, regulatory region, etc.) that influences thepathological condition or phenotype. Association studies may beconducted within the general population and are not limited to studiesperformed on related individuals in affected families (linkage studies).

Clinical trials have shown that patient response to treatment withpharmaceuticals is often heterogeneous. There is a continuing need toimprove pharmaceutical agent design and therapy. In that regard, SNPscan be used to identify patients most suited to therapy with particularpharmaceutical agents (this is often termed “pharmacogenomics”).Similarly, SNPs can be used to exclude patients from certain treatmentdue to the patient's increased likelihood of developing toxic sideeffects or their likelihood of not responding to the treatment.Pharmacogenomics can also be used in pharmaceutical research to assistthe drug development and selection process. (Linder et al. (1997),Clinical Chemistry, 43, 254; Marshall (1997), Nature Biotechnology, 15,1249; International Patent Application WO 97/40462, Spectra Biomedical;and Schafer et al. (1998), Nature Biotechnology, 16: 3).

SUMMARY OF THE INVENTION

The present invention relates to the identification of novel SNPs,unique combinations of such SNPs, haplotypes or diplotypes of SNPs thatare associated with psoriasis and in particular the increased ordecreased risk of developing psoriasis. The polymorphisms disclosedherein are directly useful as targets for the design of diagnosticreagents and the development of therapeutic agents for use in thediagnosis and treatment of psoriasis and related pathologies.

Based on the identification of SNPs associated with psoriasis, thepresent invention also provides methods of detecting these variants aswell as the design and preparation of detection reagents needed toaccomplish this task. The invention specifically provides, for example,novel SNPs in genetic sequences involved in psoriasis and relatedpathologies, isolated nucleic acid molecules (including, for example,DNA and RNA molecules) containing these SNPs, variant proteins encodedby nucleic acid molecules containing such SNPs, antibodies to theencoded variant proteins, computer-based and data storage systemscontaining the novel SNP information, methods of detecting these SNPs ina test sample, methods of identifying individuals who have an altered(i.e., increased or decreased) risk of developing psoriasis based on thepresence or absence of one or more particular nucleotides (alleles) atone or more SNP sites disclosed herein or the detection of one or moreencoded variant products (e.g., variant mRNA transcripts or variantproteins), methods of identifying individuals who are more or lesslikely to respond to a treatment (or more or less likely to experienceundesirable side effects from a treatment, etc.), methods of screeningfor compounds useful in the treatment of a disorder associated with avariant gene/protein, compounds identified by these methods, methods oftreating disorders mediated by a variant gene/protein, methods of usingthe novel SNPs of the present invention for human identification, etc.

In Tables 1-2, the present invention provides gene information,transcript sequences (SEQ ID NOS: 1-2), encoded amino acid sequences(SEQ ID NOS:3-4), genomic sequences (SEQ ID NOS:10-18), transcript-basedcontext sequences (SEQ ID NOS:5-9) and genomic-based context sequences(SEQ ID NOS:19-110) that contain the SNPs of the present invention, andextensive SNP information that includes observed alleles, allelefrequencies, populations/ethnic groups in which alleles have beenobserved, information about the type of SNP and corresponding functionaleffect, and, for cSNPs, information about the encoded polypeptideproduct. The transcript sequences (SEQ ID NOS:1-2), amino acid sequences(SEQ ID NOS:3-4), genomic sequences (SEQ ID NOS: 10-18),transcript-based SNP context sequences (SEQ ID NOS: 5-9), andgenomic-based SNP context sequences (SEQ ID NOS:19-110) are alsoprovided in the Sequence Listing.

In a specific embodiment of the present invention, SNPs that occurnaturally in the human genome are provided as isolated nucleic acidmolecules. These SNPs are associated with psoriasis and relatedpathologies. In particular the SNPs are associated with either anincreased or decreased risk of developing psoriasis. As such, they canhave a variety of uses in the diagnosis and/or treatment of psoriasisand related pathologies. One aspect of the present invention relates toan isolated nucleic acid molecule comprising a nucleotide sequence inwhich at least one nucleotide is a SNP that is propriatory to Applera,or Celera. In an alternative embodiment, a nucleic acid of the inventionis an amplified polynucleotide, which is produced by amplification of aSNP-containing nucleic acid template. In another embodiment, theinvention provides for a variant protein that is encoded by a nucleicacid molecule containing a SNP disclosed herein.

In yet another embodiment of the invention, a reagent for detecting aSNP in the context of its naturally-occurring flanking nucleotidesequences (which can be, e.g., either DNA or mRNA) is provided. Inparticular, such a reagent may be in the form of, for example, ahybridization probe or an amplification primer that is useful in thespecific detection of a SNP of interest. In an alternative embodiment, aprotein detection reagent is used to detect a variant protein that isencoded by a nucleic acid molecule containing a SNP disclosed herein. Apreferred embodiment of a protein detection reagent is an antibody or anantigen-reactive antibody fragment.

In another embodiment of the invention, applicants teach a method ofdetermining whether a human has an altered risk (either increased riskor decreased risk) of developing psoriasis or other related diseasessuch as Crohn's Diseases, comprising testing nucleic acid from saidhuman for the presence of absence of a polymorphism selected from theexon 4 LD block of IL13, wherein the presence of said polymorphismindicates that said human has an altered risk of developing psoriasis orother related diseases such as Crohn's Diseases. Examples of suchpolymorphisms are disclosed in Table 1 and Table 2.

In a further embodiment of the invention, applicants teach a method offurther correlating the presence or absence of the SNP with the alteredrisk for psoriasis or Crohn's Disease for said human.

Various embodiments of the invention also provide kits comprising SNPdetection reagents, and methods for detecting the SNPs disclosed hereinby employing detection reagents. In a specific embodiment, the presentinvention provides for a method of identifying an individual having anincreased or decreased risk of developing psoriasis by detecting thepresence or absence of one or more SNP alleles disclosed herein.Preferably, the SNP allele can be an allele of a SNP selected from thegroup consisting of rs1800925, rs20541, and rs848, or a combination ofany number of them.

In another embodiment, a method for diagnosis of psoriasis and relatedpathologies by detecting the presence or absence of one or more SNPalleles disclosed herein is provided. In another embodiment, theinvention provides for a method of identifying an individual having analtered (either increased, or, decreased) risk of developing psoriasisby detecting the presence or absence of one or more SNP haplotypesdisclosed herein.

The SNP haplotype herein can be, for example, a combination ofrs1800925(C), rs20541(C), and rs848(G), as a risk haplotype(interchangeably referred to as a susceptible haplotype). The SNPhaplotype herein can also be, for example, a combination ofrs1800925(T), rs20541(T), and rs848(T), as a protective haplotype.

Furthermore, an exemplary embodiment of the invention provides for amethod of identifying an individual having an increased risk ofdeveloping psoriasis by detecting the presence or absence of one or moreSNP haplotypes. Preferably, the SNP haplotype can be a combination ofrs1800925(C), rs20541(C), and rs848(G). An alternative exemplaryembodiment of the invention provides for a method of identifying anindividual having a decreased risk of developing psoriasis by detectingthe presence or absence of one or more SNP haplotypes. Preferably, theSNP haplotype can be a combination of rs1800925(T), rs20541(T), andrs848(T).

The nucleic acid molecules of the invention can be inserted in anexpression vector, such as to produce a variant protein in a host cell.Thus, the present invention also provides for a vector comprising aSNP-containing nucleic acid molecule, genetically-engineered host cellscontaining the vector, and methods for expressing a recombinant variantprotein using such host cells. In another specific embodiment, the hostcells, SNP-containing nucleic acid molecules, and/or variant proteinscan be used as targets in a method for screening and identifyingtherapeutic agents or pharmaceutical compounds useful in the treatmentof psoriasis and related pathologies.

An aspect of this invention is a method for treating psoriasis in ahuman subject wherein said human subject harbors a SNP, gene,transcript, and/or encoded protein identified in Tables 1-2, whichmethod comprises administering to said human subject a therapeuticallyor prophylactically effective amount of one or more agents counteractingthe effects of the disease, such as by inhibiting (or stimulating) theactivity of the gene, transcript, and/or encoded protein identified inTables 1-2.

Another aspect of this invention is a method for identifying an agentuseful in therapeutically or prophylactically treating psoriasis andrelated pathologies in a human subject wherein said human subjectharbors a SNP, gene, transcript, and/or encoded protein identified inTables 1-2, which method comprises contacting the gene, transcript, orencoded protein with a candidate agent under conditions suitable toallow formation of a binding complex between the gene, transcript, orencoded protein and the candidate agent and detecting the formation ofthe binding complex, wherein the presence of the complex identifies saidagent.

Another aspect of this invention is a method for treating psoriasis andrelated pathologies in a human subject, which method comprises:

(i) determining that said human subject harbors a SNP, gene, transcript,and/or encoded protein identified in Tables 1-2, and

(ii) administering to said subject a therapeutically or prophylacticallyeffective amount of one or more agents counteracting the effects of thedisease.

Yet another aspect of this invention is a method for evaluating thesuitability of a patient for psoriasis treatment comprising determiningthe genotype of said patient with respect to a particular set of SNPmarkers, said SNP markers comprising a plurality of individual SNPsranging from two to seven SNPs in Table 1 or Table 2, and calculating ascore using an appropriate algorithm based on the genotype of saidpatient, the resulting score being indicative of the suitability of saidpatient undergoing psoriasis treatment.

Another aspect of the invention is a method of treating a psoriasispatient comprising administering an appropriate drug in atherapeutically effective amount to said psoriasis patient whosegenotype has been shown to contain a plurality of SNPs as described inTable 1 or Table 2.

Many other uses and advantages of the present invention will be apparentto those skilled in the art upon review of the detailed description ofthe preferred embodiments herein. Solely for clarity of discussion, theinvention is described in the sections below by way of non-limitingexamples.

DESCRIPTION OF THE SEQUENCE LISTING

File CD000018ORD_SEQLIST.TXT provides the Sequence Listing in text(ASCII) format. The Sequence Listing provides the transcript sequences(SEQ ID NOS:1-2) and protein sequences (SEQ ID NOS:3-4) as shown inTable 1, and genomic sequence (SEQ ID NO:10-18) as shown in Table 2, foreach liver fibrosis-associated gene that contains one or more SNPs ofthe present invention. Also provided in the Sequence Listing are contextsequences flanking each SNP, including both transcript-based contextsequences as shown in Table 1 (SEQ ID NOS:5-9) and genomic-based contextsequences as shown in Table 2 (SEQ ID NOS:19-110). The context sequencesgenerally provide 100 bp upstream (5′) and 100 bp downstream (3′) ofeach SNP, with the SNP in the middle of the context sequence, for atotal of 200 bp of context sequence surrounding each SNP.

File CD000018ORD_SEQLIST.TXT is 716 KB in size, and was created on Nov.25, 2008.

The Sequence Listing is hereby incorporated by reference pursuant to 37CFR 1.77(b)(4).

Description of Table 1 and Table 2

Table 1 and Table 2 disclose the SNP and associatedgene/transcript/protein information of the present invention. For eachgene, Table 1 provides a header containing gene, transcript and proteininformation, followed by a transcript and protein sequence identifier(SEQ ID NO), and then SNP information regarding each SNP found in thatgene/transcript including the transcript context sequence. For each genein Table 2, a header is provided that contains gene and genomicinformation, followed by a genomic sequence identifier (SEQ ID NO) andthen SNP information regarding each SNP found in that gene, includingthe genomic context sequence.

Note that SNP markers may be included in both Table 1 and Table 2; Table1 presents the SNPs relative to their transcript sequences and encodedprotein sequences, whereas Table 2 presents the SNPs relative to theirgenomic sequences. In some instances Table 2 may also include, after thelast gene sequence, genomic sequences of one or more intergenic regions,as well as SNP context sequences and other SNP information for any SNPsthat lie within these intergenic regions. Additionally, in either Table1 or 2 a “Related Interrogated SNP” may be listed following a SNP whichis determined to be in LD with that interrogated SNP according to thegiven Power value. SNPs can be readily cross-referenced between allTables based on their Celera hCV (or, in some instances, hDV)identification numbers and/or public rs identification numbers, and tothe Sequence Listing based on their corresponding SEQ ID NOs.

The gene/transcript/protein information includes:

-   -   a gene number (1 through n, where n=the total number of genes in        the Table),    -   a gene symbol, along with an Entrez gene identification number        (Entrez Gene database, National Center for Biotechnology        Information (NCBI), National Library of Medicine, National        Institutes of Health)    -   a gene name,    -   an accession number for the transcript (e.g., RefSeq NM number,        or a Celera hCT identification number if no RefSeq NM number is        available) (Table 1 only),    -   an accession number for the protein (e.g., RefSeq NP number, or        a Celera hCP identification number if no RefSeq NP number is        available) (Table 1 only),    -   the chromosome number of the chromosome on which the gene is        located,    -   an OMIM (“Online Mendelian Inheritance in Man” database, Johns        Hopkins University/NCBI) public reference number for the gene,        and OMIM information such as alternative gene/protein name(s)        and/or symbol(s) in the OMIM entry.

Note that, due to the presence of alternative splice forms, multipletranscript/protein entries may be provided for a single gene entry inTable 1; i.e., for a single Gene Number, multiple entries may beprovided in series that differ in their transcript/protein informationand sequences.

Following the gene/transcript/protein information is a transcriptcontext sequence (Table 1), or a genomic context sequence (Table 2), foreach SNP within that gene.

After the last gene sequence, Table 2 may include additional genomicsequences of intergenic regions (in such instances, these sequences areidentified as “Intergenic region:” followed by a numericalidentification number), as well as SNP context sequences and other SNPinformation for any SNPs that lie within each intergenic region (suchSNPs are identified as “INTERGENIC” for SNP type).

Note that the transcript, protein, and transcript-based SNP contextsequences are all provided in the Sequence Listing. The transcript-basedSNP context sequences are provided in both Table 1 and also in theSequence Listing. The genomic and genomic-based SNP context sequencesare provided in the Sequence Listing. The genomic-based SNP contextsequences are provided in both Table 2 and in the Sequence Listing. SEQID NOs are indicated in Table 1 for the transcript-based contextsequences (SEQ ID NOS:5-9); SEQ ID NOs are indicated in Table 2 for thegenomic-based context sequences (SEQ ID NOS:19-110).

The SNP information includes:

-   -   Context sequence (taken from the transcript sequence in Table 1,        the genomic sequence in Table 2) with the SNP represented by its        IUB code, including 100 bp upstream (5′) of the SNP position        plus 100 bp downstream (3′) of the SNP position (the        transcript-based SNP context sequences in Table 1 are provided        in the Sequence Listing as SEQ ID NOS:5-9; the genomic-based SNP        context sequences in Table 2 are provided in the Sequence        Listing as SEQ ID NOS:19-110).    -   Celera hCV internal identification number for the SNP (in some        instances, an “hDV” number is given instead of an “hCV” number).    -   The corresponding public identification number for the SNP, the        rs number.    -   “SNP Chromosome Position” indicates the nucleotide position of        the SNP along the entire sequence of the chromosome as provided        in NCBI Genome Build 36.    -   SNP position (nucleotide position of the SNP within the given        transcript sequence (Table 1) or within the given genomic        sequence (Table 2)).    -   “Related Interrogated SNP” is the interrogated SNP with which        the listed SNP is in LD at the given value of Power.    -   SNP source (may include any combination of one or more of the        following five codes, depending on which internal sequencing        projects and/or public databases the SNP has been observed in:        “Applera”=SNP observed during the re-sequencing of genes and        regulatory regions of 39 individuals, “Celera”=SNP observed        during shotgun sequencing and assembly of the Celera human        genome sequence, “Celera Diagnostics”=SNP observed during        re-sequencing of nucleic acid samples from individuals who have        a disease, “dbSNP”=SNP observed in the dbSNP public database,        “HGBASE”=SNP observed in the HGBASE public database, “HGMD”=SNP        observed in the Human Gene Mutation Database (HGMD) public        database, “HapMap”=SNP observed in the International HapMap        Project public database, “CSNP”=SNP observed in an internal        Applied Biosystems (Foster City, Calif.) database of coding SNPS        (cSNPs).

Note that multiple “Applera” source entries for a single SNP indicatethat the same SNP was covered by multiple overlapping amplificationproducts and the re-sequencing results (e.g., observed allele counts)from each of these amplification products is being provided.

Certain SNPs from Tables 1 and 2 are SNPs for which the SNP source fallsinto one of the following three categories: 1) SNPs for which the SNPsource is only “Applera” and none other, 2) SNPs for which the SNPsource is only “Celera Diagnostics” and none other, and 3) SNPs forwhich the SNP source is both “Applera” and “Celera Diagnostics” but noneother. These SNPs have not been observed in any of the public databases(dbSNP, HGBASE, and HGMD), and were also not observed during shotgunsequencing and assembly of the Celera human genome sequence (i.e.,“Celera” SNP source). These SNPs include: hCV25597248 (transcript-basedcontext sequence SEQ ID NO:39 in Table 1, genomic-based context sequenceSEQ ID NO:113 in Table 2) and hCV25635059 (transcript-based contextsequences SEQ ID NOS:42 and 45 in Table 1; genomic-based contextsequences SEQ ID NO:123 and 335 in Table 2).

-   -   Population/allele/allele count information in the format of        [population1(first_allele,count|second_allele,count)population2(first_allele,count|second_allele,count)        total (first_allele,total count|second allele,total count)]. The        information in this field includes populations/ethnic groups in        which particular SNP alleles have been observed        (“cau”=Caucasian, “his”=Hispanic, “chn”=Chinese, and        “afr”=African-American, “jpn”=Japanese, “ind”=Indian,        “mex”=Mexican, “ain”=“American Indian, “cra”=Celera donor,        “no_pop”=no population information available), identified SNP        alleles, and observed allele counts (within each population        group and total allele counts), where available [“-” in the        allele field represents a deletion allele of an        insertion/deletion (“indel”) polymorphism (in which case the        corresponding insertion allele, which may be comprised of one or        more nucleotides, is indicated in the allele field on the        opposite side of the “I”); “-” in the count field indicates that        allele count information is not available]. For certain SNPs        from the public dbSNP database, population/ethnic information is        indicated as follows (this population information is publicly        available in dbSNP): “HISP1”=human individual DNA (anonymized        samples) from 23 individuals of self-described HISPANIC        heritage; “PAC1”=human individual DNA (anonymized samples) from        24 individuals of self-described PACIFIC RIM heritage; “CAUL        1”=human individual DNA (anonymized samples) from 31 individuals        of self-described CAUCASIAN heritage; “AFR1”=human individual        DNA (anonymized samples) from 24 individuals of self-described        AFRICAN/AFRICAN AMERICAN heritage; “P1”=human individual DNA        (anonymized samples) from 102 individuals of self-described        heritage; “PA130299515”; “SC_12_A”=SANGER 12 DNAs of Asian        origin from Corielle cell repositories, 6 of which are male and        6 female; “SC_12_C”=SANGER 12 DNAs of Caucasian origin from        Corielle cell repositories from the CEPH/UTAH library, six male        and six female; “SC_12_AA”=SANGER 12 DNAs of African-American        origin from Corielle cell repositories 6 of which are male and 6        female; “SC_95_C”=SANGER 95 DNAs of Caucasian origin from        Corielle cell repositories from the CEPH/UTAH library; and        “SC_12_CA”=Caucasians—12 DNAs from Corielle cell repositories        that are from the CEPH/UTAH library, six male and six female.

Note that for SNPs of “Applera” SNP source, genes/regulatory regions of39 individuals (20 Caucasians and 19 African Americans) werere-sequenced and, since each SNP position is represented by twochromosomes in each individual (with the exception of SNPs on X and Ychromosomes in males, for which each SNP position is represented by asingle chromosome), up to 78 chromosomes were genotyped for each SNPposition. Thus, the sum of the African-American (“afr”) allele counts isup to 38, the sum of the Caucasian allele counts (“cau”) is up to 40,and the total sum of all allele counts is up to 78.

Note that semicolons separate population/allele/count informationcorresponding to each indicated SNP source; i.e., if four SNP sourcesare indicated, such as “Celera,” “dbSNP,” “HGBASE,” and “HGMD,” thenpopulation/allele/count information is provided in four groups which areseparated by semicolons and listed in the same order as the listing ofSNP sources, with each population/allele/count information groupcorresponding to the respective SNP source based on order; thus, in thisexample, the first population/allele/count information group wouldcorrespond to the first listed SNP source (Celera) and the thirdpopulation/allele/count information group separated by semicolons wouldcorrespond to the third listed SNP source (HGBASE); ifpopulation/allele/count information is not available for any particularSNP source, then a pair of semicolons is still inserted as aplace-holder in order to maintain correspondence between the list of SNPsources and the corresponding listing of population/allele/countinformation.

-   -   SNP type (e.g., location within gene/transcript and/or predicted        functional effect) [“MISSENSE MUTATION”=SNP causes a change in        the encoded amino acid (i.e., a non-synonymous coding SNP);        “SILENT MUTATION”=SNP does not cause a change in the encoded        amino acid (i.e., a synonymous coding SNP); “STOP CODON        MUTATION”=SNP is located in a stop codon; “NONSENSE        MUTATION”=SNP creates or destroys a stop codon; “UTR 5”=SNP is        located in a 5′ UTR of a transcript; “UTR 3”=SNP is located in a        3′ UTR of a transcript; “PUTATIVE UTR 5”=SNP is located in a        putative 5′ UTR; “PUTATIVE UTR 3”=SNP is located in a putative        3′ UTR; “DONOR SPLICE SITE”=SNP is located in a donor splice        site (5′ intron boundary); “ACCEPTOR SPLICE SITE”=SNP is located        in an acceptor splice site (3′ intron boundary); “CODING        REGION”=SNP is located in a protein-coding region of the        transcript; “EXON”=SNP is located in an exon; “INTRON”=SNP is        located in an intron; “hmCS”=SNP is located in a human-mouse        conserved segment; “TFBS”=SNP is located in a transcription        factor binding site; “UNKNOWN”=SNP type is not defined;        “INTERGENIC”=SNP is intergenic, i.e., outside of any gene        boundary].    -   Protein coding information (Table 1 only), where relevant, in        the format of [protein SEQ ID NO, amino acid position, (amino        acid-1, codon1) (amino acid-2, codon2)]. The information in this        field includes SEQ ID NO of the encoded protein sequence,        position of the amino acid residue within the protein identified        by the SEQ ID NO that is encoded by the codon containing the        SNP, amino acids (represented by one-letter amino acid codes)        that are encoded by the alternative SNP alleles (in the case of        stop codons, “X” is used for the one-letter amino acid code),        and alternative codons containing the alternative SNP        nucleotides which encode the amino acid residues (thus, for        example, for missense mutation-type SNPs, at least two different        amino acids and at least two different codons are generally        indicated; for silent mutation-type SNPs, one amino acid and at        least two different codons are generally indicated, etc.). In        instances where the SNP is located outside of a protein-coding        region (e.g., in a UTR region), “None” is indicated following        the protein SEQ ID NO.

Note that SNPs can be cross-referenced between all tables herein basedon the hCV/hDV and/or rs identification number of each SNP.

Description of Table 3

Table 3 provides sequences (SEQ ID NOS:111-164) of primers that havebeen synthesized and used in the laboratory to assay certain SNPs byallele-specific PCR during the course of association studies to verifythe association of these SNPs with psoriasis (see Examples section).

Table 3 provides the following:

-   -   the column labeled “Marker” provides an hCV identification        number for each SNP.    -   the column labeled “rs number” provides the public rs        identification number for each SNP.    -   the column labeled “Alleles” designates the two alternative        alleles (i.e., nucleotides) at the SNP site. These alleles are        targeted by the allele-specific primers (the allele-specific        primers are shown as Primer 1 and Primer 2). Note that alleles        may be presented in Table 3 based on a different orientation        (i.e., the reverse complement) relative to how the same alleles        are presented in Tables 1-2.    -   the column labeled “Primer 1 (Allele-Specific Primer)” provides        an allele-specific primer that is specific for an allele        designated in the “Alleles” column.    -   the column labeled “Primer 2 (Allele-Specific Primer)” provides        an allele-specific primer that is specific for the other allele        designated in the “Alleles” column.    -   the column labeled “Common Primer” provides a common primer that        is used in conjunction with each of the allele-specific primers        (i.e., Primer 1 and Primer 2) and which hybridizes at a site        away from the SNP position.

All primer sequences are given in the 5′ to 3′ direction.

Each of the nucleotides designated in the “Alleles” column matches or isthe reverse complement of (depending on the orientation of the primerrelative to the designated allele) the 3′ nucleotide of theallele-specific primer (i.e., either Primer 1 or Primer 2) that isspecific for that allele.

Description of Table 4

Table 4 provides a list of LD SNPs that are related to and derived fromcertain interrogated SNPs. The interrogated SNPs, which are shown incolumn 1 (which indicates the hCV identification numbers of eachinterrogated SNP) and column 2 (which indicates the public rsidentification numbers of each interrogated SNP) of Table 4, arestatistically significantly associated with psoriasis as shown in thetables. These LD SNPs are provided as an example of SNPs which can alsoserve as markers for disease association based on their being in LD withan interrogated SNP. The criteria and process of selecting such LD SNPs,including the calculation of the r² value and the r² threshold value,are described in Example Two, below.

In Table 4, the column labeled “Interrogated SNP” presents each markeras identified by its unique hCV identification number. The columnlabeled “Interrogated rs” presents the publicly known identifier rsnumber for the corresponding hCV number. The column labeled “LD SNP”presents the hCV numbers of the LD SNPs that are derived from theircorresponding interrogated SNPs. The column labeled “LD SNP rs” presentsthe publicly known rs number for the corresponding hCV number. Thecolumn labeled “Power” presents the level of power where the r²threshold is set. For example, when power is set at 0.51, the thresholdr² value calculated therefrom is the minimum r² that an LD SNP must havein reference to an interrogated SNP, in order for the LD SNP to beclassified as a marker capable of being associated with a diseasephenotype at greater than 51% probability. The column labeled “Thresholdr²” presents the minimum value of r² that an LD SNP must meet inreference to an interrogated SNP in order to qualify as an LD SNP. Thecolumn labeled “r²” presents the actual r² value of the LD SNP inreference to the interrogated SNP to which it is related.

Descriptions of Tables 5-16

Table 5 provides statistical results for the association of the IL13SNPs rs1800925, rs20541, and rs848 with psoriasis. All three SNPs wereindividually genotyped using allele-specific real-time PCR as previouslydescribed⁹. Positions for each SNP are given according to genomic contigNT_034772.5 (Entrez Nucleotide). The minor allele is listed first,followed by the position in National Center for BiotechnologyInformation Genome Build 36.2 and then the major allele. All sampleswere white of Northern European extraction and are described in detailelsewhere⁹ (Sample set 1: 467 cases/460 controls; sample set 2: 498cases/498 controls; sample set 3: 481 cases/424 controls).Hardy-Weinberg exact P-values were calculated according to the formulaof Weir.¹⁰ Fisher's exact P-values were calculated for allelic data.Two-tailed P-values are presented for Sample Set 1; one-tailed P-valuesare given for Sample Sets 2 and 3. Combined P-values were calculatedusing a Fisher's combined P-value, or omnibus method. Genotypic P-valuesfor the individual sample sets were calculated using theWilliam's-corrected G test.¹¹ As with the allelic analysis, Sample Set 1P-values are two-tailed; Sample Set 2 and 3 P-values are one-tailed.Odds ratios were calculated for the minor allele. Combined or joint ORswere calculated using a Mantel-Haenszel common OR.

Table 6 provides statistical results for the association of three-markerIL13 haplotypes with psoriasis. The order of SNPs isrs1800925-rs20541-rs848. The Haplo.Stats package¹² was used to estimatehaplotype frequencies from unphased data, treating cases and controlsseparately, and to test for association between haplotypes and diseasestatus. Global P-values were also calculated and all P-values wereadjusted for haplotype estimation error. Two tailed P-values arepresented for sample set 1; one-tailed P-values are presented for SampleSets 2 and 3. P-values were combined using Fisher's combined probabilitymethod. Mantel-Haenszel joint odds ratios (ORMH) were calculated foreach haplotype.

Table 7 provides HLA-cytokine pathway psoriasis relative risk estimates.HLA-C genotypes were partitioned into *0602 carriers and noncarriers.IL12B (rs3212227 and 6887695) and IL23R (rs7530511 and rs11209026)diplotypes⁹ were combined with IL13 (rs1800925) genotypes and classifiedinto risk groups (Very High to Low) as outlined below Table 7. Psoriasisprevalence was set at 0.03. The probability of psoriasis conditioned oneach multi-locus genotype—P(MLG), was calculated using Bayes' theorem.The P(MLG) was divided by the unconditioned psoriasis risk (diseaseprevalence) to obtain the relative risk values. Confidence intervalswere calculated using 10,000 replicates of a Monte Carlo simulation. Thescaled relative risk (SRR) was calculated by setting the lowest riskcategory equal to 1.

Throughout Tables 5-16, “OR” refers to the odds ratio, “95% CI” refersto the 95% confidence interval for the odds ratio, “MAF” refers to theminor allele frequency, and “HWE” refers to Hardy-Weinberg equilibrium.

Odds ratios (OR) greater than one indicate that a given allele (orcombination of alleles such as a haplotype, diplotype, or two-locusdiplotype) is a risk allele, whereas odds ratios less than one indicatethat a given allele is a non-risk allele (which may also be referred toas a protective allele). For a given risk (i.e., susceptible) allele,the other alternative allele at the SNP position (which can be derivedfrom the information provided in Tables 1-2, for example) may beconsidered a non-risk (i.e., protective) allele. For a given non-risk(i.e., protective) allele, the other alternative allele at the SNPposition may be considered a risk allele.

Tables 8-16 are described in detail in the Examples section below.

BRIEF DESCRIPTION OF THE FIGURES

FIG. 1 shows a HLA-cytokine pathway psoriasis relative risk plot. Thescaled relative risk of each multi-locus genotype combination is graphedusing the data from sample set 1. HLA-C genotypes were determined aspreviously described⁹ and aggregated into *0602 carriers andnoncarriers. Psoriasis-associated diplotypes at IL12B (rs3212227 andrs6887695) and IL23R (rs753511 and rs11209026)⁹ were combined withgenotypes at rs1800925 (5′ of IL13) and partitioned into four cytokinepathway categories: very high risk, high risk, moderate risk and lowrisk (as described in the description of Table 7). Psoriasis prevalenceof 0.03 was assumed. Conditional independence between the loci was alsoassumed [Three separate analyses—a genotype-based squared correlationcoefficient, the Multifactor dimensionality reduction (MDR) program,¹⁷and a Monte Carlo simulation—substantiated this assumption and providedno evidence for significant interaction effects between these markers.].Expected frequencies of the multi-locus genotype combinations arepresented for both affected and unaffected populations and are listedabove each bar (affected/unaffected). The relative risk estimates werescaled with respect to the lowest risk category, which was set at 1.00.

FIG. 2A shows a schematic representation of P-values of SNPs tested inthe three sample sets individually (SS1, SS2 and SS3) and combined(meta). A total of 93 SNPs were tested in sample set 1; 12 SNPs weretested in sample sets 2 and 3. rs1800925, rs20541 and rs848, which werepreviously reported to be associated with psoriasis (21), were tested inall three sample sets. A gene map is shown at the bottom, based on theNCBI b36 genome assembly.

FIG. 2B shows Inter-marker LD of the 93 markers in sample set 1. D′values are shown in the top right triangle, and r² values are in thebottom triangle. The D′ and r² values were calculated using both casesand controls of sample set 1.

DETAILED DESCRIPTION OF THE INVENTION

The present invention provides SNPs associated with psoriasis andrelated pathologies, nucleic acid molecules containing SNPs, methods andreagents for the detection of the SNPs disclosed herein, uses of theseSNPs for the development of detection reagents, and assays or kits thatutilize such reagents. The psoriasis-associated SNPs disclosed hereinare useful for diagnosing, screening for, and evaluating predispositionto psoriasis, including an increased or decreased risk of developingpsoriasis, the rate of progression of psoriasis, and related pathologiesin humans.

Furthermore, such SNPs and their encoded products are useful targets forthe development of therapeutic agents.

A large number of SNPs have been identified from re-sequencing DNA from39 individuals, and they are indicated as “Applera” SNP source in Tables1-2. Their allele frequencies observed in each of the Caucasian andAfrican-American ethnic groups are provided. Additional SNPs includedherein were previously identified during shotgun sequencing and assemblyof the human genome, and they are indicated as “Celera” SNP source inTables 1-2. Furthermore, the information provided in Table 1-2,particularly the allele frequency information obtained from 39individuals and the identification of the precise position of each SNPwithin each gene/transcript, allows haplotypes (i.e., groups of SNPsthat are co-inherited) to be readily inferred. The present inventionencompasses SNP haplotypes, as well as individual SNPs.

Thus, the present invention provides individual SNPs associated withpsoriasis, as well as combinations of SNPs and haplotypes in geneticregions associated with psoriasis, polymorphic/variant transcriptsequences (SEQ ID NOS:1-2) and genomic sequences (SEQ ID NOS:10-18)containing SNPs, encoded amino acid sequences (SEQ ID NOS: 3-4), andboth transcript-based SNP context sequences (SEQ ID NOS: 5-9) andgenomic-based SNP context sequences (SEQ ID NOS:19-110) (transcriptsequences, protein sequences, and transcript-based SNP context sequencesare provided in Table 1 and the Sequence Listing; genomic sequences andgenomic-based SNP context sequences are provided in Table 2 and theSequence Listing), methods of detecting these polymorphisms in a testsample, methods of determining the risk of an individual of having ordeveloping psoriasis, methods of screening for compounds useful fortreating disorders associated with a variant gene/protein such aspsoriasis, compounds identified by these screening methods, methods ofusing the disclosed SNPs to select a treatment strategy, methods oftreating a disorder associated with a variant gene/protein (i.e.,therapeutic methods), and methods of using the SNPs of the presentinvention for human identification.

The present invention provides novel SNPs associated with psoriasis andrelated pathologies, as well as SNPs that were previously known in theart, but were not previously known to be associated with psoriasis.Accordingly, the present invention provides novel compositions andmethods based on the novel SNPs disclosed herein, and also providesnovel methods of using the known, but previously unassociated, SNPs inmethods relating to psoriasis (e.g., for diagnosing psoriasis, etc.). InTables 1-2, known SNPs are identified based on the public database inwhich they have been observed, which is indicated as one or more of thefollowing SNP types: “dbSNP”=SNP observed in dbSNP, “HGBASE”=SNPobserved in HGBASE, and “HGMD”=SNP observed in the Human Gene MutationDatabase (HGMD). Novel SNPs for which the SNP source is only “Applera”and none other, i.e., those that have not been observed in any publicdatabases and which were also not observed during shotgun sequencing andassembly of the Celera human genome sequence (i.e., “Celera” SNPsource), are indicated in the tables.

Particular SNP alleles of the present invention can be associated witheither an increased risk of having or developing psoriasis and relatedpathologies, or a decreased risk of having or developing psoriasis. SNPalleles that are associated with a decreased risk of having ordeveloping psoriasis may be referred to as “protective” alleles, and SNPalleles that are associated with an increased risk of having ordeveloping psoriasis may be referred to as “susceptibility” alleles,“risk” alleles, or “risk factors”. Thus, whereas certain SNPs (or theirencoded products) can be assayed to determine whether an individualpossesses a SNP allele that is indicative of an increased risk of havingor developing psoriasis (i.e., a susceptibility allele), other SNPs (ortheir encoded products) can be assayed to determine whether anindividual possesses a SNP allele that is indicative of a decreased riskof having or developing psoriasis (i.e., a protective allele).Similarly, particular SNP alleles of the present invention can beassociated with either an increased or decreased likelihood ofresponding to a particular treatment or therapeutic compound, or anincreased or decreased likelihood of experiencing toxic effects from aparticular treatment or therapeutic compound. The term “altered” may beused herein to encompass either of these two possibilities (e.g., anincreased or a decreased risk/likelihood).

Those skilled in the art will readily recognize that nucleic acidmolecules may be double-stranded molecules and that reference to aparticular site on one strand refers, as well, to the corresponding siteon a complementary strand. In defining a SNP position, SNP allele, ornucleotide sequence, reference to an adenine, a thymine (uridine), acytosine, or a guanine at a particular site on one strand of a nucleicacid molecule also defines the thymine (uridine), adenine, guanine, orcytosine (respectively) at the corresponding site on a complementarystrand of the nucleic acid molecule. Thus, reference may be made toeither strand in order to refer to a particular SNP position, SNPallele, or nucleotide sequence. Probes and primers, may be designed tohybridize to either strand and SNP genotyping methods disclosed hereinmay generally target either strand. Throughout the specification, inidentifying a SNP position, reference is generally made to theprotein-encoding strand, only for the purpose of convenience.

References to variant peptides, polypeptides, or proteins of the presentinvention include peptides, polypeptides, proteins, or fragmentsthereof, that contain at least one amino acid residue that differs fromthe corresponding amino acid sequence of the art-knownpeptide/polypeptide/protein (the art-known protein may beinterchangeably referred to as the “wild-type”, “reference”, or “normal”protein). Such variant peptides/polypeptides/proteins can result from acodon change caused by a nonsynonymous nucleotide substitution at aprotein-coding SNP position (i.e., a missense mutation) disclosed by thepresent invention. Variant peptides/polypeptides/proteins of the presentinvention can also result from a nonsense mutation, i.e., a SNP thatcreates a premature stop codon, a SNP that generates a read-throughmutation by abolishing a stop codon, or due to any SNP disclosed by thepresent invention that otherwise alters the structure,function/activity, or expression of a protein, such as a SNP in aregulatory region (e.g. a promoter or enhancer) or a SNP that leads toalternative or defective splicing, such as a SNP in an intron or a SNPat an exon/intron boundary. As used herein, the terms “polypeptide”,“peptide”, and “protein” are used interchangeably.

IL12B, IL23R, and HLA-C

The SNPs provided herein, particularly rs1800925, rs20541, and rs848[including the risk haplotype of rs1800925(C), rs20541(C), and rs848(G);and the protective haplotype of rs1800925(T), rs20541(T), and rs848(T)],can be combined with other genetic variants, such as to increase thepower to determine psoriasis risk. In certain preferred embodiments,SNPs rs1800925, rs20541, and rs848 are combined with any or all of HLA-C(e.g., HLA-C variant *0602), IL12B SNPs, and IL23 SNPs.

Exemplary IL12B and IL23R variants which can be used in conjunction withrs1800925, rs20541, and/or rs848 include any of the following SNPs,haplotypes, diplotypes, and two-locus diplotypes, and any combination ofthese:

SNPs rs321227, rs3212220, rs7709212, and rs6887695.

The psoriasis risk haplotype rs3212227(A) and rs6887695(G).

The psoriasis protective haplotype rs3212227(C) and rs6887695(C).

The psoriasis risk haplotype rs11209026(G) and rs7530511(C).

A SNP diplotype which is a combination of two copies of the riskhaplotype, rs3212227(A)/rs6887695(G).

A SNP diplotype which is a combination of two copies of the protectivehaplotype, rs3212227(C)/rs6887695(C).

A SNP diplotype which is a combination of two copies of the riskhaplotype rs11209026(G)/rs7530511(C).

A two-locus diplotype which is a combination ofrs3212227(A)/rs6887695(G)/rs11209026(G)/rs7530511(C).

Further information regarding the above IL12B and IL23R SNPs,haplotypes, and diplotypes, including allele information and exemplarynucleotide sequences, is disclosed in Cargill et al., “A large-scalegenetic association study confirms IL12B and leads to the identificationof IL23R as psoriasis risk genes”, Am J Hum Genet. 2007 February;80(2):273-90, which is incorporated herein by reference.

IL13 Therapeutics/Pharmacogenomics in Inflammatory and AutoimmuneDisorders

Exemplary embodiments of the invention provide SNPs in IL13 that areassociated with psoriasis (as shown in the tables). These SNPs have avariety of therapeutic and pharmacogenomic uses related to the treatmentof psoriasis, as well as other inflammatory and autoimmune disorderssuch as Crohn's disease and bronchial hyperresponsiveness/atopy/asthma.The psoriasis-associated SNPs provided herein may be used, for example,to determine variability between different individuals in their responseto an inflammatory or autoimmune disease therapy (e.g., a psoriasistherapy or a therapy for Crohn's disease, bronchialhyperresponsiveness/atopy/asthma, or other inflammatory or autoimmunedisorder) such as to predict whether an individual will respondpositively to a particular therapy, to determine the most effectivetherapeutic agent (e.g., antibody, small molecule compound, nucleic acidagent, etc.) to use to treat an individual, to determine whether aparticular therapeutic agent should or should not be administered to anindividual (e.g., by predicting whether the individual is likely topositively respond to the therapy or by predicting whether theindividual will experience toxic or other undesirable side effects or isunlikely to respond to the therapy), or to determine the therapeuticregimen to use for an individual such as the dosage or frequency ofdosing of a therapeutic agent for a particular individual. Therapeuticagents that directly modulate IL13 may be used to treat psoriasis orother inflammatory/autoimmune disorders and, furthermore, therapeuticagents that target proteins that interact with IL13 or are otherwise inIL13 pathways may be used to indirectly modulate IL13 to thereby treatpsoriasis or other inflammatory/autimmune disorders. Any therapeuticagents such as these may be used in conjunction with the SNPs providedherein.

For example, the IL13 psoriasis-associated SNPs provided herein may beused to predict whether an individual will respond positively toanti-IL13 antibody therapy and/or to determine the most effective dosageof this therapy. This facilitates decision making by medicalpractitioners, such as in deciding whether to administer this therapy toa particular individual or select another therapy that may be bettersuited to the individual, or to use a particular dosage, dosingschedule, or to modify other aspects of a therapeutic regimen toeffectively treat the individual, for example.

In addition to medical treatment, these uses may also be applied, forexample, in the context of clinical trials of a therapeutic agent (e.g.,a therapeutic agent that targets IL13 for the treatment of psoriasis,Crohn's disease, bronchial hyperresponsiveness/atopy/asthma, or otherinflammatory or autoimmune disorder), such as to include particularindividuals in a clinical trial who are predicted to positively respondto the therapeutic agent based on the SNPs provided herein and/or toexclude particular individuals from a clinical trial who are predictedto not positively respond to the therapeutic agent based on the SNPsprovided herein. By using the SNPs provided herein to target atherapeutic agent to individuals who are more likely to positivelyrespond to the agent, the therapeutic agent is more likely to succeed inclinical trials by showing positive efficacy and to therefore satisfythe FDA requirements for approval. Additionally, individuals who aremore likely to experience toxic or other undesirable side effects may beexcluded from being administered the therapeutic agent. Furthermore, byusing the SNPs provided herein to determine an effective dosage ordosing frequency, for example, the therapeutic agent may be less likelyto exhibit toxicity or other undesirable side effects, as well as morelikely to achieve positive efficacy.

Isolated Nucleic Acid Molecules and SNP Detection Reagents & Kits

Tables 1 and 2 provide a variety of information about each SNP of thepresent invention that is associated with psoriasis, including thetranscript sequences (SEQ ID NOS:1-2), genomic sequences (SEQ IDNOS:10-18), and protein sequences (SEQ ID NOS:3-4) of the encoded geneproducts (with the SNPs indicated by IUB codes in the nucleic acidsequences). In addition, Tables 1 and 2 include SNP context sequences,which generally include 100 nucleotide upstream (5′) plus 100nucleotides downstream (3′) of each SNP position (SEQ ID NOS:5-9)correspond to transcript-based SNP context sequences disclosed in Table1, and SEQ ID NOS:19-110 correspond to genomic-based context sequencesdisclosed in Table 2), the alternative nucleotides (alleles) at each SNPposition, and additional information about the variant where relevant,such as SNP type (coding, missense, splice site, UTR, etc.), humanpopulations in which the SNP was observed, observed allele frequencies,information about the encoded protein, etc.

Isolated Nucleic Acid Molecules

The present invention provides isolated nucleic acid molecules thatcontain one or more SNPs disclosed Table 1 and/or Table 2. Preferredisolated nucleic acid molecules contain one or more SNPs identified asApplera or Celera proprietary. Isolated nucleic acid moleculescontaining one or more SNPs disclosed in at least one of Tables 1-2 maybe interchangeably referred to throughout the present text as“SNP-containing nucleic acid molecules”. Isolated nucleic acid moleculesmay optionally encode a full-length variant protein or fragment thereof.The isolated nucleic acid molecules of the present invention alsoinclude probes and primers (which are described in greater detail belowin the section entitled “SNP Detection Reagents”), which may be used forassaying the disclosed SNPs, and isolated full-length genes,transcripts, cDNA molecules, and fragments thereof, which may be usedfor such purposes as expressing an encoded protein.

As used herein, an “isolated nucleic acid molecule” generally is onethat contains a SNP of the present invention or one that hybridizes tosuch molecule such as a nucleic acid with a complementary sequence, andis separated from most other nucleic acids present in the natural sourceof the nucleic acid molecule. Moreover, an “isolated” nucleic acidmolecule, such as a cDNA molecule containing a SNP of the presentinvention, can be substantially free of other cellular material, orculture medium when produced by recombinant techniques, or chemicalprecursors or other chemicals when chemically synthesized. A nucleicacid molecule can be fused to other coding or regulatory sequences andstill be considered “isolated”. Nucleic acid molecules present innon-human transgenic animals, which do not naturally occur in theanimal, are also considered “isolated”. For example, recombinant DNAmolecules contained in a vector are considered “isolated”. Furtherexamples of “isolated” DNA molecules include recombinant DNA moleculesmaintained in heterologous host cells, and purified (partially orsubstantially) DNA molecules in solution. Isolated RNA molecules includein vivo or in vitro RNA transcripts of the isolated SNP-containing DNAmolecules of the present invention. Isolated nucleic acid moleculesaccording to the present invention further include such moleculesproduced synthetically.

Generally, an isolated SNP-containing nucleic acid molecule comprisesone or more SNP positions disclosed by the present invention withflanking nucleotide sequences on either side of the SNP positions. Aflanking sequence can include nucleotide residues that are naturallyassociated with the SNP site and/or heterologous nucleotide sequences.Preferably the flanking sequence is up to about 500, 300, 100, 60, 50,30, 25, 20, 15, 10, 8, or 4 nucleotides (or any other length in-between)on either side of a SNP position, or as long as the full-length gene orentire protein-coding sequence (or any portion thereof such as an exon),especially if the SNP-containing nucleic acid molecule is to be used toproduce a protein or protein fragment.

For full-length genes and entire protein-coding sequences, a SNPflanking sequence can be, for example, up to about 5 KB, 4 KB, 3 KB, 2KB, 1 KB on either side of the SNP. Furthermore, in such instances, theisolated nucleic acid molecule comprises exonic sequences (includingprotein-coding and/or non-coding exonic sequences), but may also includeintronic sequences. Thus, any protein coding sequence may be eithercontiguous or separated by introns. The important point is that thenucleic acid is isolated from remote and unimportant flanking sequencesand is of appropriate length such that it can be subjected to thespecific manipulations or uses described herein such as recombinantprotein expression, preparation of probes and primers for assaying theSNP position, and other uses specific to the SNP-containing nucleic acidsequences.

An isolated SNP-containing nucleic acid molecule can comprise, forexample, a full-length gene or transcript, such as a gene isolated fromgenomic DNA (e.g., by cloning or PCR amplification), a cDNA molecule, oran mRNA transcript molecule. Polymorphic transcript sequences areprovided in Table 1 and in the Sequence Listing (SEQ ID NOS:1-2), andpolymorphic genomic sequences are provided in Table 2 and in theSequence Listing (SEQ ID NOS:10-18). Furthermore, fragments of suchfull-length genes and transcripts that contain one or more SNPsdisclosed herein are also encompassed by the present invention, and suchfragments may be used, for example, to express any part of a protein,such as a particular functional domain or an antigenic epitope.

Thus, the present invention also encompasses fragments of the nucleicacid sequences provided in Tables 1-2 (transcript sequences are providedin Table 1 as SEQ ID NOS:1-2, genomic sequences are provided in Table 2as SEQ ID NOS:10-18, transcript-based SNP context sequences are providedin Table 1 as SEQ ID NO:5-9, and genomic-based SNP context sequences areprovided in Table 2 as SEQ ID NO:19-110) and their complements. Afragment typically comprises a contiguous nucleotide sequence at leastabout 8 or more nucleotides, more preferably at least about 12 or morenucleotides, and even more preferably at least about 16 or morenucleotides. Further, a fragment could comprise at least about 18, 20,22, 25, 30, 40, 50, 60, 80, 100, 150, 200, 250 or 500 (or any othernumber in-between) nucleotides in length. The length of the fragmentwill be based on its intended use. For example, the fragment can encodeepitope-bearing regions of a variant peptide or regions of a variantpeptide that differ from the normal/wild-type protein, or can be usefulas a polynucleotide probe or primer. Such fragments can be isolatedusing the nucleotide sequences provided in Table 1 and/or Table 2 forthe synthesis of a polynucleotide probe. A labeled probe can then beused, for example, to screen a cDNA library, genomic DNA library, ormRNA to isolate nucleic acid corresponding to the coding region.Further, primers can be used in amplification reactions, such as forpurposes of assaying one or more SNPs sites or for cloning specificregions of a gene.

An isolated nucleic acid molecule of the present invention furtherencompasses a SNP-containing polynucleotide that is the product of anyone of a variety of nucleic acid amplification methods, which are usedto increase the copy numbers of a polynucleotide of interest in anucleic acid sample. Such amplification methods are well known in theart, and they include but are not limited to, polymerase chain reaction(PCR) (U.S. Pat. Nos. 4,683,195; and 4,683,202; PCR Technology:Principles and Applications for DNA Amplification, ed. H. A. Erlich,Freeman Press, NY, NY, 1992), ligase chain reaction (LCR) (Wu andWallace, Genomics 4:560, 1989; Landegren et al., Science 241:1077,1988), strand displacement amplification (SDA) (U.S. Pat. Nos.5,270,184; and 5,422,252), transcription-mediated amplification (TMA)(U.S. Pat. No. 5,399,491), linked linear amplification (LLA) (U.S. Pat.No. 6,027,923), and the like, and isothermal amplification methods suchas nucleic acid sequence based amplification (NASBA), and self-sustainedsequence replication (Guatelli et al., Proc. Natl. Acad. Sci. USA 87:1874, 1990). Based on such methodologies, a person skilled in the artcan readily design primers in any suitable regions 5′ and 3′ to a SNPdisclosed herein. Such primers may be used to amplify DNA of any lengthso long that it contains the SNP of interest in its sequence.

As used herein, an “amplified polynucleotide” of the invention is aSNP-containing nucleic acid molecule whose amount has been increased atleast two fold by any nucleic acid amplification method performed invitro as compared to its starting amount in a test sample. In otherpreferred embodiments, an amplified polynucleotide is the result of atleast ten fold, fifty fold, one hundred fold, one thousand fold, or eventen thousand fold increase as compared to its starting amount in a testsample. In a typical PCR amplification, a polynucleotide of interest isoften amplified at least fifty thousand fold in amount over theunamplified genomic DNA, but the precise amount of amplification neededfor an assay depends on the sensitivity of the subsequent detectionmethod used.

Generally, an amplified polynucleotide is at least about 16 nucleotidesin length. More typically, an amplified polynucleotide is at least about20 nucleotides in length. In a preferred embodiment of the invention, anamplified polynucleotide is at least about 30 nucleotides in length. Ina more preferred embodiment of the invention, an amplifiedpolynucleotide is at least about 32, 40, 45, 50, or 60 nucleotides inlength. In yet another preferred embodiment of the invention, anamplified polynucleotide is at least about 100, 200, 300, 400, or 500nucleotides in length. While the total length of an amplifiedpolynucleotide of the invention can be as long as an exon, an intron orthe entire gene where the SNP of interest resides, an amplified productis typically up to about 1,000 nucleotides in length (although certainamplification methods may generate amplified products greater than 1000nucleotides in length). More preferably, an amplified polynucleotide isnot greater than about 600-700 nucleotides in length. It is understoodthat irrespective of the length of an amplified polynucleotide, a SNP ofinterest may be located anywhere along its sequence.

In a specific embodiment of the invention, the amplified product is atleast about 201 nucleotides in length, comprises one of thetranscript-based context sequences or the genomic-based contextsequences shown in Tables 1-2. Such a product may have additionalsequences on its 5′ end or 3′ end or both. In another embodiment, theamplified product is about 101 nucleotides in length, and it contains aSNP disclosed herein. Preferably, the SNP is located at the middle ofthe amplified product (e.g., at position 101 in an amplified productthat is 201 nucleotides in length, or at position 51 in an amplifiedproduct that is 101 nucleotides in length), or within 1, 2, 3, 4, 5, 6,7, 8, 9, 10, 12, 15, or 20 nucleotides from the middle of the amplifiedproduct (however, as indicated above, the SNP of interest may be locatedanywhere along the length of the amplified product).

The present invention provides isolated nucleic acid molecules thatcomprise, consist of, or consist essentially of one or morepolynucleotide sequences that contain one or more SNPs disclosed herein,complements thereof, and SNP-containing fragments thereof.

Accordingly, the present invention provides nucleic acid molecules thatconsist of any of the nucleotide sequences shown in Table 1 and/or Table2 (transcript sequences are provided in Table 1 as SEQ ID NOS:1-2,genomic sequences are provided in Table 2 as SEQ ID NOS:10-18,transcript-based SNP context sequences are provided in Table 1 as SEQ IDNO:5-9, and genomic-based SNP context sequences are provided in Table 2as SEQ ID NO:19-110), or any nucleic acid molecule that encodes any ofthe variant proteins provided in Table 1 (SEQ ID NOS:3-4). A nucleicacid molecule consists of a nucleotide sequence when the nucleotidesequence is the complete nucleotide sequence of the nucleic acidmolecule.

The present invention further provides nucleic acid molecules thatconsist essentially of any of the nucleotide sequences shown in Table 1and/or Table 2 (transcript sequences are provided in Table 1 as SEQ IDNOS:1-2, genomic sequences are provided in Table 2 as SEQ ID NOS:10-18,transcript-based SNP context sequences are provided in Table 1 as SEQ IDNO:5-9, and genomic-based SNP context sequences are provided in Table 2as SEQ ID NO:19-110), or any nucleic acid molecule that encodes any ofthe variant proteins provided in Table 1 (SEQ ID NOS:3-4). A nucleicacid molecule consists essentially of a nucleotide sequence when such anucleotide sequence is present with only a few additional nucleotideresidues in the final nucleic acid molecule.

The present invention further provides nucleic acid molecules thatcomprise any of the nucleotide sequences shown in Table 1 and/or Table 2or a SNP-containing fragment thereof (transcript sequences are providedin Table 1 as SEQ ID NOS:1-2, genomic sequences are provided in Table 2as SEQ ID NOS:10-18, transcript-based SNP context sequences are providedin Table 1 as SEQ ID NO:5-9, and genomic-based SNP context sequences areprovided in Table 2 as SEQ ID NO:19-110), or any nucleic acid moleculethat encodes any of the variant proteins provided in Table 1 (SEQ IDNOS:3-4). A nucleic acid molecule comprises a nucleotide sequence whenthe nucleotide sequence is at least part of the final nucleotidesequence of the nucleic acid molecule. In such a fashion, the nucleicacid molecule can be only the nucleotide sequence or have additionalnucleotide residues, such as residues that are naturally associated withit or heterologous nucleotide sequences. Such a nucleic acid moleculecan have one to a few additional nucleotides or can comprise many moreadditional nucleotides. A brief description of how various types ofthese nucleic acid molecules can be readily made and isolated isprovided below, and such techniques are well known to those of ordinaryskill in the art (Sambrook and Russell, 2000, Molecular Cloning: ALaboratory Manual, Cold Spring Harbor Press, NY).

The isolated nucleic acid molecules can encode mature proteins plusadditional amino or carboxyl-terminal amino acids or both, or aminoacids interior to the mature peptide (when the mature form has more thanone peptide chain, for instance). Such sequences may play a role inprocessing of a protein from precursor to a mature form, facilitateprotein trafficking, prolong or shorten protein half-life, or facilitatemanipulation of a protein for assay or production. As generally is thecase in situ, the additional amino acids may be processed away from themature protein by cellular enzymes.

Thus, the isolated nucleic acid molecules include, but are not limitedto, nucleic acid molecules having a sequence encoding a peptide alone, asequence encoding a mature peptide and additional coding sequences suchas a leader or secretory sequence (e.g., a pre-pro or pro-proteinsequence), a sequence encoding a mature peptide with or withoutadditional coding sequences, plus additional non-coding sequences, forexample introns and non-coding 5′ and 3′ sequences such as transcribedbut untranslated sequences that play a role in, for example,transcription, mRNA processing (including splicing and polyadenylationsignals), ribosome binding, and/or stability of mRNA. In addition, thenucleic acid molecules may be fused to heterologous marker sequencesencoding, for example, a peptide that facilitates purification.

Isolated nucleic acid molecules can be in the form of RNA, such as mRNA,or in the form DNA, including cDNA and genomic DNA, which may beobtained, for example, by molecular cloning or produced by chemicalsynthetic techniques or by a combination thereof (Sambrook and Russell,2000, Molecular Cloning: A Laboratory Manual, Cold Spring Harbor Press,NY). Furthermore, isolated nucleic acid molecules, particularly SNPdetection reagents such as probes and primers, can also be partially orcompletely in the form of one or more types of nucleic acid analogs,such as peptide nucleic acid (PNA) (U.S. Pat. Nos. 5,539,082; 5,527,675;5,623,049; 5,714,331). The nucleic acid, especially DNA, can bedouble-stranded or single-stranded. Single-stranded nucleic acid can bethe coding strand (sense strand) or the complementary non-coding strand(antisense strand). DNA, RNA, or PNA segments can be assembled, forexample, from fragments of the human genome (in the case of DNA or RNA)or single nucleotides, short oligonucleotide linkers, or from a seriesof oligonucleotides, to provide a synthetic nucleic acid molecule.Nucleic acid molecules can be readily synthesized using the sequencesprovided herein as a reference; oligonucleotide and PNA oligomersynthesis techniques are well known in the art (see, e.g., Corey,“Peptide nucleic acids: expanding the scope of nucleic acidrecognition”, Trends Biotechnol. 1997 June; 15(6):224-9, and Hyrup etal., “Peptide nucleic acids (PNA): synthesis, properties and potentialapplications”, Bioorg Med Chem. 1996 January; 4(1):5-23). Furthermore,large-scale automated oligonucleotide/PNA synthesis (including synthesison an array or bead surface or other solid support) can readily beaccomplished using commercially available nucleic acid synthesizers,such as the Applied Biosystems (Foster City, Calif.) 3900High-Throughput DNA Synthesizer or Expedite 8909 Nucleic Acid SynthesisSystem, and the sequence information provided herein.

The present invention encompasses nucleic acid analogs that containmodified, synthetic, or non-naturally occurring nucleotides orstructural elements or other alternative/modified nucleic acidchemistries known in the art. Such nucleic acid analogs are useful, forexample, as detection reagents (e.g., primers/probes) for detecting oneor more SNPs identified in Table 1 and/or Table 2. Furthermore,kits/systems (such as beads, arrays, etc.) that include these analogsare also encompassed by the present invention. For example, PNAoligomers that are based on the polymorphic sequences of the presentinvention are specifically contemplated. PNA oligomers are analogs ofDNA in which the phosphate backbone is replaced with a peptide-likebackbone (Lagriffoul et al., Bioorganic & Medicinal Chemistry Letters,4: 1081-1082 (1994), Petersen et W., Bioorganic & Medicinal ChemistryLetters, 6: 793-796 (1996), Kumar et al., Organic Letters 3(9):1269-1272 (2001), WO96/04000). PNA hybridizes to complementary RNA orDNA with higher affinity and specificity than conventionaloligonucleotides and oligonucleotide analogs. The properties of PNAenable novel molecular biology and biochemistry applicationsunachievable with traditional oligonucleotides and peptides.

Additional examples of nucleic acid modifications that improve thebinding properties and/or stability of a nucleic acid include the use ofbase analogs such as inosine, intercalators (U.S. Pat. No. 4,835,263)and the minor groove binders (U.S. Pat. No. 5,801,115). Thus, referencesherein to nucleic acid molecules, SNP-containing nucleic acid molecules,SNP detection reagents (e.g., probes and primers),oligonucleotides/polynucleotides include PNA oligomers and other nucleicacid analogs. Other examples of nucleic acid analogs andalternative/modified nucleic acid chemistries known in the art aredescribed in Current Protocols in Nucleic Acid Chemistry, John Wiley &Sons, N.Y. (2002).

The present invention further provides nucleic acid molecules thatencode fragments of the variant polypeptides disclosed herein as well asnucleic acid molecules that encode obvious variants of such variantpolypeptides. Such nucleic acid molecules may be naturally occurring,such as paralogs (different locus) and orthologs (different organism),or may be constructed by recombinant DNA methods or by chemicalsynthesis. Non-naturally occurring variants may be made by mutagenesistechniques, including those applied to nucleic acid molecules, cells, ororganisms. Accordingly, the variants can contain nucleotidesubstitutions, deletions, inversions and insertions (in addition to theSNPs disclosed in Tables 1-2). Variation can occur in either or both thecoding and non-coding regions. The variations can produce conservativeand/or non-conservative amino acid substitutions.

Further variants of the nucleic acid molecules disclosed in Tables 1-2,such as naturally occurring allelic variants (as well as orthologs andparalogs) and synthetic variants produced by mutagenesis techniques, canbe identified and/or produced using methods well known in the art. Suchfurther variants can comprise a nucleotide sequence that shares at least70-80%, 80-85%, 85-90%, 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, or 99%sequence identity with a nucleic acid sequence disclosed in Table 1and/or Table 2 (or a fragment thereof) and that includes a novel SNPallele disclosed in Table 1 and/or Table 2. Further, variants cancomprise a nucleotide sequence that encodes a polypeptide that shares atleast 70-80%, 80-85%, 85-90%, 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, or99% sequence identity with a polypeptide sequence disclosed in Table 1(or a fragment thereof) and that includes a novel SNP allele disclosedin Table 1 and/or Table 2. Thus, an aspect of the present invention thatis specifically contemplated are isolated nucleic acid molecules thathave a certain degree of sequence variation compared with the sequencesshown in Tables 1-2, but that contain a novel SNP allele disclosedherein. In other words, as long as an isolated nucleic acid moleculecontains a novel SNP allele disclosed herein, other portions of thenucleic acid molecule that flank the novel SNP allele can vary to somedegree from the specific transcript, genomic, and context sequencesshown in Tables 1-2, and can encode a polypeptide that varies to somedegree from the specific polypeptide sequences shown in Table 1.

To determine the percent identity of two amino acid sequences or twonucleotide sequences of two molecules that share sequence homology, thesequences are aligned for optimal comparison purposes (e.g., gaps can beintroduced in one or both of a first and a second amino acid or nucleicacid sequence for optimal alignment and non-homologous sequences can bedisregarded for comparison purposes). In a preferred embodiment, atleast 30%, 40%, 50%, 60%, 70%, 80%, or 90% or more of the length of areference sequence is aligned for comparison purposes. The amino acidresidues or nucleotides at corresponding amino acid positions ornucleotide positions are then compared. When a position in the firstsequence is occupied by the same amino acid residue or nucleotide as thecorresponding position in the second sequence, then the molecules areidentical at that position (as used herein, amino acid or nucleic acid“identity” is equivalent to amino acid or nucleic acid “homology”). Thepercent identity between the two sequences is a function of the numberof identical positions shared by the sequences, taking into account thenumber of gaps, and the length of each gap, which need to be introducedfor optimal alignment of the two sequences.

The comparison of sequences and determination of percent identitybetween two sequences can be accomplished using a mathematicalalgorithm. (Computational Molecular Biology, Lesk, A. M., ed., OxfordUniversity Press, New York, 1988; Biocomputing: Informatics and GenomeProjects, Smith, D. W., ed., Academic Press, New York, 1993; ComputerAnalysis of Sequence Data, Part 1, Griffin, A. M., and Griffin, H. G.,eds., Humana Press, New Jersey, 1994; Sequence Analysis in MolecularBiology, von Heinje, G., Academic Press, 1987; and Sequence AnalysisPrimer, Gribskov, M. and Devereux, J., eds., M Stockton Press, New York,1991). In a preferred embodiment, the percent identity between two aminoacid sequences is determined using the Needleman and Wunsch algorithm(J. Mol. Biol. (48):444-453 (1970)) which has been incorporated into theGAP program in the GCG software package, using either a Blossom 62matrix or a PAM250 matrix, and a gap weight of 16, 14, 12, 10, 8, 6, or4 and a length weight of 1, 2, 3, 4, 5, or 6.

In yet another preferred embodiment, the percent identity between twonucleotide sequences is determined using the GAP program in the GCGsoftware package (Devereux, J., et al., Nucleic Acids Res. 12(1):387(1984)), using a NWSgapdna.CMP matrix and a gap weight of 40, 50, 60,70, or 80 and a length weight of 1, 2, 3, 4, 5, or 6. In anotherembodiment, the percent identity between two amino acid or nucleotidesequences is determined using the algorithm of E. Myers and W. Miller(CABIOS, 4:11-17 (1989)) which has been incorporated into the ALIGNprogram (version 2.0), using a PAM120 weight residue table, a gap lengthpenalty of 12, and a gap penalty of 4.

The nucleotide and amino acid sequences of the present invention canfurther be used as a “query sequence” to perform a search againstsequence databases to, for example, identify other family members orrelated sequences. Such searches can be performed using the NBLAST andXBLAST programs (version 2.0) of Altschul, et al. (J. Mol. Biol.215:403-10 (1990)). BLAST nucleotide searches can be performed with theNBLAST program, score=100, wordlength=12 to obtain nucleotide sequenceshomologous to the nucleic acid molecules of the invention. BLAST proteinsearches can be performed with the XBLAST program, score=50,wordlength=3 to obtain amino acid sequences homologous to the proteinsof the invention. To obtain gapped alignments for comparison purposes,Gapped BLAST can be utilized as described in Altschul et al. (NucleicAcids Res. 25(17):3389-3402 (1997)). When utilizing BLAST and gappedBLAST programs, the default parameters of the respective programs (e.g.,XBLAST and NBLAST) can be used. In addition to BLAST, examples of othersearch and sequence comparison programs used in the art include, but arenot limited to, FASTA (Pearson, Methods Mol. Biol. 25, 365-389 (1994))and KERR (Dufresne et al., Nat Biotechnol 2002 December;20(12):1269-71). For further information regarding bioinformaticstechniques, see Current Protocols in Bioinformatics, John Wiley & Sons,Inc., N.Y.

The present invention further provides non-coding fragments of thenucleic acid molecules disclosed in Table 1 and/or Table 2. Preferrednon-coding fragments include, but are not limited to, promotersequences, enhancer sequences, intronic sequences, 5′ untranslatedregions (UTRs), 3′ untranslated regions, gene modulating sequences andgene termination sequences. Such fragments are useful, for example, incontrolling heterologous gene expression and in developing screens toidentify gene-modulating agents.

SNP Detection Reagents

In a specific aspect of the present invention, the SNPs disclosed inTable 1 and/or Table 2, and their associated transcript sequences(provided in Table 1 as SEQ ID NOS:1-2), genomic sequences (provided inTable 2 as SEQ ID NOS:10-18), and context sequences (transcript-basedcontext sequences are provided in Table 1 as SEQ ID NOS:5-9;genomic-based context sequences are provided in Table 2 as SEQ IDNOS:19-110), can be used for the design of SNP detection reagents. Asused herein, a “SNP detection reagent” is a reagent that specificallydetects a specific target SNP position disclosed herein, and that ispreferably specific for a particular nucleotide (allele) of the targetSNP position (i.e., the detection reagent preferably can differentiatebetween different alternative nucleotides at a target SNP position,thereby allowing the identity of the nucleotide present at the targetSNP position to be determined). Typically, such detection reagenthybridizes to a target SNP-containing nucleic acid molecule bycomplementary base-pairing in a sequence specific manner, anddiscriminates the target variant sequence from other nucleic acidsequences such as an art-known form in a test sample. An example of adetection reagent is a probe that hybridizes to a target nucleic acidcontaining one or more of the SNPs provided in Table 1 and/or Table 2.In a preferred embodiment, such a probe can differentiate betweennucleic acids having a particular nucleotide (allele) at a target SNPposition from other nucleic acids that have a different nucleotide atthe same target SNP position. In addition, a detection reagent mayhybridize to a specific region 5′ and/or 3′ to a SNP position,particularly a region corresponding to the context sequences provided inTable 1 and/or Table 2 (transcript-based context sequences are providedin Table 1 as SEQ ID NOS:5-9; genomic-based context sequences areprovided in Table 2 as SEQ ID NOS:19-110). Another example of adetection reagent is a primer which acts as an initiation point ofnucleotide extension along a complementary strand of a targetpolynucleotide. The SNP sequence information provided herein is alsouseful for designing primers, e.g. allele-specific primers, to amplify(e.g., using PCR) any SNP of the present invention.

In one preferred embodiment of the invention, a SNP detection reagent isan isolated or synthetic DNA or RNA polynucleotide probe or primer orPNA oligomer, or a combination of DNA, RNA and/or PNA, that hybridizesto a segment of a target nucleic acid molecule containing a SNPidentified in Table 1 and/or Table 2. A detection reagent in the form ofa polynucleotide may optionally contain modified base analogs,intercalators or minor groove binders. Multiple detection reagents suchas probes may be, for example, affixed to a solid support (e.g., arraysor beads) or supplied in solution (e.g., probe/primer sets for enzymaticreactions such as PCR, RT-PCR, TaqMan assays, or primer-extensionreactions) to form a SNP detection kit.

A probe or primer typically is a substantially purified oligonucleotideor PNA oligomer. Such oligonucleotide typically comprises a region ofcomplementary nucleotide sequence that hybridizes under stringentconditions to at least about 8, 10, 12, 16, 18, 20, 22, 25, 30, 40, 50,55, 60, 65, 70, 80, 90, 100, 120 (or any other number in-between) ormore consecutive nucleotides in a target nucleic acid molecule.Depending on the particular assay, the consecutive nucleotides caneither include the target SNP position, or be a specific region in closeenough proximity 5′ and/or 3′ to the SNP position to carry out thedesired assay.

Other preferred primer and probe sequences can readily be determinedusing the transcript sequences (SEQ ID NOS:1-2), genomic sequences (SEQID NOS:10-18), and SNP context sequences (transcript-based contextsequences are provided in Table 1 as SEQ ID NOS:5-9; genomic-basedcontext sequences are provided in Table 2 as SEQ ID NOS:19-110)disclosed in the Sequence Listing and in Tables 1-2. It will be apparentto one of skill in the art that such primers and probes are directlyuseful as reagents for genotyping the SNPs of the present invention, andcan be incorporated into any kit/system format.

In order to produce a probe or primer specific for a targetSNP-containing sequence, the gene/transcript and/or context sequencesurrounding the SNP of interest is typically examined using a computeralgorithm which starts at the 5′ or at the 3′ end of the nucleotidesequence. Typical algorithms will then identify oligomers of definedlength that are unique to the gene/SNP context sequence, have a GCcontent within a range suitable for hybridization, lack predictedsecondary structure that may interfere with hybridization, and/orpossess other desired characteristics or that lack other undesiredcharacteristics.

A primer or probe of the present invention is typically at least about 8nucleotides in length. In one embodiment of the invention, a primer or aprobe is at least about 10 nucleotides in length. In a preferredembodiment, a primer or a probe is at least about 12 nucleotides inlength. In a more preferred embodiment, a primer or probe is at leastabout 16, 17, 18, 19, 20, 21, 22, 23, 24 or 25 nucleotides in length.While the maximal length of a probe can be as long as the targetsequence to be detected, depending on the type of assay in which it isemployed, it is typically less than about 50, 60, 65, or 70 nucleotidesin length. In the case of a primer, it is typically less than about 30nucleotides in length. In a specific preferred embodiment of theinvention, a primer or a probe is within the length of about 18 andabout 28 nucleotides. However, in other embodiments, such as nucleicacid arrays and other embodiments in which probes are affixed to asubstrate, the probes can be longer, such as on the order of 30-70, 75,80, 90, 100, or more nucleotides in length (see the section belowentitled “SNP Detection Kits and Systems”).

For analyzing SNPs, it may be appropriate to use oligonucleotidesspecific for alternative SNP alleles. Such oligonucleotides which detectsingle nucleotide variations in target sequences may be referred to bysuch terms as “allele-specific oligonucleotides”, “allele-specificprobes”, or “allele-specific primers”. The design and use ofallele-specific probes for analyzing polymorphisms is described in,e.g., Mutation Detection A Practical Approach, ed. Cotton et al. OxfordUniversity Press, 1998; Saiki et al., Nature 324, 163-166 (1986);Dattagupta, EP235,726; and Saiki, WO 89/11548.

While the design of each allele-specific primer or probe depends onvariables such as the precise composition of the nucleotide sequencesflanking a SNP position in a target nucleic acid molecule, and thelength of the primer or probe, another factor in the use of primers andprobes is the stringency of the condition under which the hybridizationbetween the probe or primer and the target sequence is performed. Higherstringency conditions utilize buffers with lower ionic strength and/or ahigher reaction temperature, and tend to require a more perfect matchbetween probe/primer and a target sequence in order to form a stableduplex. If the stringency is too high, however, hybridization may notoccur at all. In contrast, lower stringency conditions utilize bufferswith higher ionic strength and/or a lower reaction temperature, andpermit the formation of stable duplexes with more mismatched basesbetween a probe/primer and a target sequence. By way of example and notlimitation, exemplary conditions for high stringency hybridizationconditions using an allele-specific probe are as follows:Prehybridization with a solution containing 5× standard saline phosphateEDTA (SSPE), 0.5% NaDodSO₄ (SDS) at 55° C., and incubating probe withtarget nucleic acid molecules in the same solution at the sametemperature, followed by washing with a solution containing 2×SSPE, and0.1% SDS at 55° C. or room temperature.

Moderate stringency hybridization conditions may be used forallele-specific primer extension reactions with a solution containing,e.g., about 50 mM KCl at about 46° C. Alternatively, the reaction may becarried out at an elevated temperature such as 60° C. In anotherembodiment, a moderately stringent hybridization condition suitable foroligonucleotide ligation assay (OLA) reactions wherein two probes areligated if they are completely complementary to the target sequence mayutilize a solution of about 100 mM KCl at a temperature of 46° C.

In a hybridization-based assay, allele-specific probes can be designedthat hybridize to a segment of target DNA from one individual but do nothybridize to the corresponding segment from another individual due tothe presence of different polymorphic forms (e.g., alternative SNPalleles/nucleotides) in the respective DNA segments from the twoindividuals. Hybridization conditions should be sufficiently stringentthat there is a significant detectable difference in hybridizationintensity between alleles, and preferably an essentially binaryresponse, whereby a probe hybridizes to only one of the alleles orsignificantly more strongly to one allele. While a probe may be designedto hybridize to a target sequence that contains a SNP site such that theSNP site aligns anywhere along the sequence of the probe, the probe ispreferably designed to hybridize to a segment of the target sequencesuch that the SNP site aligns with a central position of the probe(e.g., a position within the probe that is at least three nucleotidesfrom either end of the probe). This design of probe generally achievesgood discrimination in hybridization between different allelic forms.

In another embodiment, a probe or primer may be designed to hybridize toa segment of target DNA such that the SNP aligns with either the 5′ mostend or the 3′ most end of the probe or primer. In a specific preferredembodiment which is particularly suitable for use in a oligonucleotideligation assay (U.S. Pat. No. 4,988,617), the 3′most nucleotide of theprobe aligns with the SNP position in the target sequence.

Oligonucleotide probes and primers may be prepared by methods well knownin the art. Chemical synthetic methods include, but are limited to, thephosphotriester method described by Narang et al., 1979, Methods inEnzymology 68:90; the phosphodiester method described by Brown et al.,1979, Methods in Enzymology 68:109, the diethylphosphoamidate methoddescribed by Beaucage et al., 1981, Tetrahedron Letters 22:1859; and thesolid support method described in U.S. Pat. No. 4,458,066.

Allele-specific probes are often used in pairs (or, less commonly, insets of 3 or 4, such as if a SNP position is known to have 3 or 4alleles, respectively, or to assay both strands of a nucleic acidmolecule for a target SNP allele), and such pairs may be identicalexcept for a one nucleotide mismatch that represents the allelicvariants at the SNP position. Commonly, one member of a pair perfectlymatches a reference form of a target sequence that has a more common SNPallele (i.e., the allele that is more frequent in the target population)and the other member of the pair perfectly matches a form of the targetsequence that has a less common SNP allele (i.e., the allele that israrer in the target population). In the case of an array, multiple pairsof probes can be immobilized on the same support for simultaneousanalysis of multiple different polymorphisms.

In one type of PCR-based assay, an allele-specific primer hybridizes toa region on a target nucleic acid molecule that overlaps a SNP positionand only primes amplification of an allelic form to which the primerexhibits perfect complementarity (Gibbs, 1989, Nucleic Acid Res. 172427-2448). Typically, the primer's 3′-most nucleotide is aligned withand complementary to the SNP position of the target nucleic acidmolecule. This primer is used in conjunction with a second primer thathybridizes at a distal site. Amplification proceeds from the twoprimers, producing a detectable product that indicates which allelicform is present in the test sample. A control is usually performed witha second pair of primers, one of which shows a single base mismatch atthe polymorphic site and the other of which exhibits perfectcomplementarity to a distal site. The single-base mismatch preventsamplification or substantially reduces amplification efficiency, so thateither no detectable product is formed or it is formed in lower amountsor at a slower pace. The method generally works most effectively whenthe mismatch is at the 3′-most position of the oligonucleotide (i.e.,the 3′-most position of the oligonucleotide aligns with the target SNPposition) because this position is most destabilizing to elongation fromthe primer (see, e.g., WO 93/22456). This PCR-based assay can beutilized as part of the TaqMan assay, described below.

In a specific embodiment of the invention, a primer of the inventioncontains a sequence substantially complementary to a segment of a targetSNP-containing nucleic acid molecule except that the primer has amismatched nucleotide in one of the three nucleotide positions at the3′-most end of the primer, such that the mismatched nucleotide does notbase pair with a particular allele at the SNP site. In a preferredembodiment, the mismatched nucleotide in the primer is the second fromthe last nucleotide at the 3′-most position of the primer. In a morepreferred embodiment, the mismatched nucleotide in the primer is thelast nucleotide at the 3′-most position of the primer.

In another embodiment of the invention, a SNP detection reagent of theinvention is labeled with a fluorogenic reporter dye that emits adetectable signal. While the preferred reporter dye is a fluorescentdye, any reporter dye that can be attached to a detection reagent suchas an oligonucleotide probe or primer is suitable for use in theinvention. Such dyes include, but are not limited to, Acridine, AMCA,BODIPY, Cascade Blue, Cy2, Cy3, Cy5, Cy7, Dabcyl, Edans, Eosin,Erythrosin, Fluorescein, 6-Fam, Tet, Joe, Hex, Oregon Green, Rhodamine,Rhodol Green, Tamra, Rox, and Texas Red.

In yet another embodiment of the invention, the detection reagent may befurther labeled with a quencher dye such as Tamra, especially when thereagent is used as a self-quenching probe such as a TaqMan (U.S. Pat.Nos. 5,210,015 and 5,538,848) or Molecular Beacon probe (U.S. Pat. Nos.5,118,801 and 5,312,728), or other stemless or linear beacon probe(Livak et al., 1995, PCR Method Appl. 4:357-362; Tyagi et al., 1996,Nature Biotechnology 14: 303-308; Nazarenko et al., 1997, Nucl. AcidsRes. 25:2516-2521; U.S. Pat. Nos. 5,866,336 and 6,117,635).

The detection reagents of the invention may also contain other labels,including but not limited to, biotin for streptavidin binding, haptenfor antibody binding, and oligonucleotide for binding to anothercomplementary oligonucleotide such as pairs of zipcodes.

The present invention also contemplates reagents that do not contain (orthat are complementary to) a SNP nucleotide identified herein but thatare used to assay one or more SNPs disclosed herein. For example,primers that flank, but do not hybridize directly to a target SNPposition provided herein are useful in primer extension reactions inwhich the primers hybridize to a region adjacent to the target SNPposition (i.e., within one or more nucleotides from the target SNPsite). During the primer extension reaction, a primer is typically notable to extend past a target SNP site if a particular nucleotide(allele) is present at that target SNP site, and the primer extensionproduct can be detected in order to determine which SNP allele ispresent at the target SNP site. For example, particular ddNTPs aretypically used in the primer extension reaction to terminate primerextension once a ddNTP is incorporated into the extension product (aprimer extension product which includes a ddNTP at the 3′-most end ofthe primer extension product, and in which the ddNTP is a nucleotide ofa SNP disclosed herein, is a composition that is specificallycontemplated by the present invention). Thus, reagents that bind to anucleic acid molecule in a region adjacent to a SNP site and that areused for assaying the SNP site, even though the bound sequences do notnecessarily include the SNP site itself, are also contemplated by thepresent invention.

SNP Detection Kits and Systems

A person skilled in the art will recognize that, based on the SNP andassociated sequence information disclosed herein, detection reagents canbe developed and used to assay any SNP of the present inventionindividually or in combination, and such detection reagents can bereadily incorporated into one of the established kit or system formatswhich are well known in the art. The terms “kits” and “systems”, as usedherein in the context of SNP detection reagents, are intended to referto such things as combinations of multiple SNP detection reagents, orone or more SNP detection reagents in combination with one or more othertypes of elements or components (e.g., other types of biochemicalreagents, containers, packages such as packaging intended for commercialsale, substrates to which SNP detection reagents are attached,electronic hardware components, etc.). Accordingly, the presentinvention further provides SNP detection kits and systems, including butnot limited to, packaged probe and primer sets (e.g., TaqManprobe/primer sets), arrays/microarrays of nucleic acid molecules, andbeads that contain one or more probes, primers, or other detectionreagents for detecting one or more SNPs of the present invention. Thekits/systems can optionally include various electronic hardwarecomponents; for example, arrays (“DNA chips”) and microfluidic systems(“lab-on-a-chip” systems) provided by various manufacturers typicallycomprise hardware components. Other kits/systems (e.g., probe/primersets) may not include electronic hardware components, but may becomprised of, for example, one or more SNP detection reagents (alongwith, optionally, other biochemical reagents) packaged in one or morecontainers.

In some embodiments, a SNP detection kit typically contains one or moredetection reagents and other components (e.g., a buffer, enzymes such asDNA polymerases or ligases, chain extension nucleotides such asdeoxynucleotide triphosphates, and in the case of Sanger-type DNAsequencing reactions, chain terminating nucleotides, positive controlsequences, negative control sequences, and the like) necessary to carryout an assay or reaction, such as amplification and/or detection of aSNP-containing nucleic acid molecule. A kit may further contain meansfor determining the amount of a target nucleic acid, and means forcomparing the amount with a standard, and can comprise instructions forusing the kit to detect the SNP-containing nucleic acid molecule ofinterest. In one embodiment of the present invention, kits are providedwhich contain the necessary reagents to carry out one or more assays todetect one or more SNPs disclosed herein. In a preferred embodiment ofthe present invention, SNP detection kits/systems are in the form ofnucleic acid arrays, or compartmentalized kits, includingmicrofluidic/lab-on-a-chip systems.

SNP detection kits/systems may contain, for example, one or more probes,or pairs of probes, that hybridize to a nucleic acid molecule at or neareach target SNP position. Multiple pairs of allele-specific probes maybe included in the kit/system to simultaneously assay large numbers ofSNPs, at least one of which is a SNP of the present invention. In somekits/systems, the allele-specific probes are immobilized to a substratesuch as an array or bead. For example, the same substrate can compriseallele-specific probes for detecting at least 1; 10; 100; 1000; 10,000;100,000 (or any other number in-between) or substantially all of theSNPs shown in Table 1 and/or Table 2.

The terms “arrays”, “microarrays”, and “DNA chips” are used hereininterchangeably to refer to an array of distinct polynucleotides affixedto a substrate, such as glass, plastic, paper, nylon or other type ofmembrane, filter, chip, or any other suitable solid support. Thepolynucleotides can be synthesized directly on the substrate, orsynthesized separate from the substrate and then affixed to thesubstrate. In one embodiment, the microarray is prepared and usedaccording to the methods described in U.S. Pat. No. 5,837,832, Chee etal., PCT application WO95/11995 (Chee et al.), Lockhart, D. J. et al.(1996; Nat. Biotech. 14: 1675-1680) and Schena, M. et al. (1996; Proc.Natl. Acad. Sci. 93: 10614-10619), all of which are incorporated hereinin their entirety by reference. In other embodiments, such arrays areproduced by the methods described by Brown et al., U.S. Pat. No.5,807,522.

Nucleic acid arrays are reviewed in the following references: Zammatteoet al., “New chips for molecular biology and diagnostics”, BiotechnolAnnu Rev. 2002; 8:85-101; Sosnowski et al., “Active microelectronicarray system for DNA hybridization, genotyping and pharmacogenomicapplications”, Psychiatr Genet. 2002 December; 12(4):181-92; Heller,“DNA microarray technology: devices, systems, and applications”, AnnuRev Biomed Eng. 2002; 4:129-53. Epub 2002 Mar. 22; Kolchinsky et al.,“Analysis of SNPs and other genomic variations using gel-based chips”,Hum Mutat. 2002 April; 19(4):343-60; and McGall et al., “High-densitygenechip oligonucleotide probe arrays”, Adv Biochem Eng Biotechnol.2002; 77:21-42.

Any number of probes, such as allele-specific probes, may be implementedin an array, and each probe or pair of probes can hybridize to adifferent SNP position. In the case of polynucleotide probes, they canbe synthesized at designated areas (or synthesized separately and thenaffixed to designated areas) on a substrate using a light-directedchemical process. Each DNA chip can contain, for example, thousands tomillions of individual synthetic polynucleotide probes arranged in agrid-like pattern and miniaturized (e.g., to the size of a dime).Preferably, probes are attached to a solid support in an ordered,addressable array.

A microarray can be composed of a large number of unique,single-stranded polynucleotides, usually either synthetic antisensepolynucleotides or fragments of cDNAs, fixed to a solid support. Typicalpolynucleotides are preferably about 6-60 nucleotides in length, morepreferably about 15-30 nucleotides in length, and most preferably about18-25 nucleotides in length. For certain types of microarrays or otherdetection kits/systems, it may be preferable to use oligonucleotidesthat are only about 7-20 nucleotides in length. In other types ofarrays, such as arrays used in conjunction with chemiluminescentdetection technology, preferred probe lengths can be, for example, about15-80 nucleotides in length, preferably about 50-70 nucleotides inlength, more preferably about 55-65 nucleotides in length, and mostpreferably about 60 nucleotides in length. The microarray or detectionkit can contain polynucleotides that cover the known 5′ or 3′ sequenceof a gene/transcript or target SNP site, sequential polynucleotides thatcover the full-length sequence of a gene/transcript; or uniquepolynucleotides selected from particular areas along the length of atarget gene/transcript sequence, particularly areas corresponding to oneor more SNPs disclosed in Table 1 and/or Table 2. Polynucleotides usedin the microarray or detection kit can be specific to a SNP or SNPs ofinterest (e.g., specific to a particular SNP allele at a target SNPsite, or specific to particular SNP alleles at multiple different SNPsites), or specific to a polymorphic gene/transcript orgenes/transcripts of interest.

Hybridization assays based on polynucleotide arrays rely on thedifferences in hybridization stability of the probes to perfectlymatched and mismatched target sequence variants. For SNP genotyping, itis generally preferable that stringency conditions used in hybridizationassays are high enough such that nucleic acid molecules that differ fromone another at as little as a single SNP position can be differentiated(e.g., typical SNP hybridization assays are designed so thathybridization will occur only if one particular nucleotide is present ata SNP position, but will not occur if an alternative nucleotide ispresent at that SNP position). Such high stringency conditions may bepreferable when using, for example, nucleic acid arrays ofallele-specific probes for SNP detection. Such high stringencyconditions are described in the preceding section, and are well known tothose skilled in the art and can be found in, for example, CurrentProtocols in Molecular Biology, John Wiley & Sons, N.Y. (1989),6.3.1-6.3.6.

In other embodiments, the arrays are used in conjunction withchemiluminescent detection technology. The following patents and patentapplications, which are all hereby incorporated by reference, provideadditional information pertaining to chemiluminescent detection: U.S.patent application Ser. Nos. 10/620,332 and 10/620,333 describechemiluminescent approaches for microarray detection; U.S. Pat. Nos.6,124,478, 6,107,024, 5,994,073, 5,981,768, 5,871,938, 5,843,681,5,800,999, and 5,773,628 describe methods and compositions of dioxetanefor performing chemiluminescent detection; and U.S. publishedapplication US2002/0110828 discloses methods and compositions formicroarray controls.

In one embodiment of the invention, a nucleic acid array can comprise anarray of probes of about 15-25 nucleotides in length. In furtherembodiments, a nucleic acid array can comprise any number of probes, inwhich at least one probe is capable of detecting one or more SNPsdisclosed in Table 1 and/or Table 2, and/or at least one probe comprisesa fragment of one of the sequences selected from the group consisting ofthose disclosed in Table 1, Table 2, the Sequence Listing, and sequencescomplementary thereto, said fragment comprising at least about 8consecutive nucleotides, preferably 10, 12, 15, 16, 18, 20, morepreferably 22, 25, 30, 40, 47, 50, 55, 60, 65, 70, 80, 90, 100, or moreconsecutive nucleotides (or any other number in-between) and containing(or being complementary to) a novel SNP allele disclosed in Table 1and/or Table 2. In some embodiments, the nucleotide complementary to theSNP site is within 5, 4, 3, 2, or 1 nucleotide from the center of theprobe, more preferably at the center of said probe.

A polynucleotide probe can be synthesized on the surface of thesubstrate by using a chemical coupling procedure and an ink jetapplication apparatus, as described in PCT application WO95/251116(Baldeschweiler et al.) which is incorporated herein in its entirety byreference. In another aspect, a “gridded” array analogous to a dot (orslot) blot may be used to arrange and link cDNA fragments oroligonucleotides to the surface of a substrate using a vacuum system,thermal, UV, mechanical or chemical bonding procedures. An array, suchas those described above, may be produced by hand or by using availabledevices (slot blot or dot blot apparatus), materials (any suitable solidsupport), and machines (including robotic instruments), and may contain8, 24, 96, 384, 1536, 6144 or more polynucleotides, or any other numberwhich lends itself to the efficient use of commercially availableinstrumentation.

Using such arrays or other kits/systems, the present invention providesmethods of identifying the SNPs disclosed herein in a test sample. Suchmethods typically involve incubating a test sample of nucleic acids withan array comprising one or more probes corresponding to at least one SNPposition of the present invention, and assaying for binding of a nucleicacid from the test sample with one or more of the probes. Conditions forincubating a SNP detection reagent (or a kit/system that employs one ormore such SNP detection reagents) with a test sample vary. Incubationconditions depend on such factors as the format employed in the assay,the detection methods employed, and the type and nature of the detectionreagents used in the assay. One skilled in the art will recognize thatany one of the commonly available hybridization, amplification and arrayassay formats can readily be adapted to detect the SNPs disclosedherein.

A SNP detection kit/system of the present invention may includecomponents that are used to prepare nucleic acids from a test sample forthe subsequent amplification and/or detection of a SNP-containingnucleic acid molecule. Such sample preparation components can be used toproduce nucleic acid extracts (including DNA and/or RNA), proteins ormembrane extracts from any bodily fluids (such as blood, serum, plasma,urine, saliva, phlegm, gastric juices, semen, tears, sweat, etc.), skin,hair, cells (especially nucleated cells), biopsies, buccal swabs ortissue specimens. The test samples used in the above-described methodswill vary based on such factors as the assay format, nature of thedetection method, and the specific tissues, cells or extracts used asthe test sample to be assayed. Methods of preparing nucleic acids,proteins, and cell extracts are well known in the art and can be readilyadapted to obtain a sample that is compatible with the system utilized.Automated sample preparation systems for extracting nucleic acids from atest sample are commercially available, and examples are Qiagen'sBioRobot 9600, Applied Biosystems' PRISM™ 6700 sample preparationsystem, and Roche Molecular Systems' COBAS AmpliPrep System.

Another form of kit contemplated by the present invention is acompartmentalized kit. A compartmentalized kit includes any kit in whichreagents are contained in separate containers. Such containers include,for example, small glass containers, plastic containers, strips ofplastic, glass or paper, or arraying material such as silica. Suchcontainers allow one to efficiently transfer reagents from onecompartment to another compartment such that the test samples andreagents are not cross-contaminated, or from one container to anothervessel not included in the kit, and the agents or solutions of eachcontainer can be added in a quantitative fashion from one compartment toanother or to another vessel. Such containers may include, for example,one or more containers which will accept the test sample, one or morecontainers which contain at least one probe or other SNP detectionreagent for detecting one or more SNPs of the present invention, one ormore containers which contain wash reagents (such as phosphate bufferedsaline, Tris-buffers, etc.), and one or more containers which containthe reagents used to reveal the presence of the bound probe or other SNPdetection reagents. The kit can optionally further comprise compartmentsand/or reagents for, for example, nucleic acid amplification or otherenzymatic reactions such as primer extension reactions, hybridization,ligation, electrophoresis (preferably capillary electrophoresis), massspectrometry, and/or laser-induced fluorescent detection. The kit mayalso include instructions for using the kit. Exemplary compartmentalizedkits include microfluidic devices known in the art (see, e.g., Weigl etal., “Lab-on-a-chip for drug development”, Adv Drug Deliv Rev. 2003 Feb.24; 55(3):349-77). In such microfluidic devices, the containers may bereferred to as, for example, microfluidic “compartments”, “chambers”, or“channels”.

Microfluidic devices, which may also be referred to as “lab-on-a-chip”systems, biomedical micro-electro-mechanical systems (bioMEMs), ormulticomponent integrated systems, are exemplary kits/systems of thepresent invention for analyzing SNPs. Such systems miniaturize andcompartmentalize processes such as probe/target hybridization, nucleicacid amplification, and capillary electrophoresis reactions in a singlefunctional device. Such microfluidic devices typically utilize detectionreagents in at least one aspect of the system, and such detectionreagents may be used to detect one or more SNPs of the presentinvention. One example of a microfluidic system is disclosed in U.S.Pat. No. 5,589,136, which describes the integration of PCR amplificationand capillary electrophoresis in chips. Exemplary microfluidic systemscomprise a pattern of microchannels designed onto a glass, silicon,quartz, or plastic wafer included on a microchip. The movements of thesamples may be controlled by electric, electroosmotic or hydrostaticforces applied across different areas of the microchip to createfunctional microscopic valves and pumps with no moving parts. Varyingthe voltage can be used as a means to control the liquid flow atintersections between the micro-machined channels and to change theliquid flow rate for pumping across different sections of the microchip.See, for example, U.S. Pat. No. 6,153,073, Dubrow et al., and U.S. Pat.No. 6,156,181, Parce et al.

For genotyping SNPs, an exemplary microfluidic system may integrate, forexample, nucleic acid amplification, primer extension, capillaryelectrophoresis, and a detection method such as laser inducedfluorescence detection. In a first step of an exemplary process forusing such an exemplary system, nucleic acid samples are amplified,preferably by PCR. Then, the amplification products are subjected toautomated primer extension reactions using ddNTPs (specific fluorescencefor each ddNTP) and the appropriate oligonucleotide primers to carry outprimer extension reactions which hybridize just upstream of the targetedSNP. Once the extension at the 3′ end is completed, the primers areseparated from the unincorporated fluorescent ddNTPs by capillaryelectrophoresis. The separation medium used in capillary electrophoresiscan be, for example, polyacrylamide, polyethyleneglycol or dextran. Theincorporated ddNTPs in the single nucleotide primer extension productsare identified by laser-induced fluorescence detection. Such anexemplary microchip can be used to process, for example, at least 96 to384 samples, or more, in parallel.

Uses of Nucleic Acid Molecules

The nucleic acid molecules of the present invention have a variety ofuses, especially in the diagnosis and treatment of psoriasis and relatedpathologies. For example, the nucleic acid molecules are useful ashybridization probes, such as for genotyping SNPs in messenger RNA,transcript, cDNA, genomic DNA, amplified DNA or other nucleic acidmolecules, and for isolating full-length cDNA and genomic clonesencoding the variant peptides disclosed in Table 1 as well as theirorthologs.

A probe can hybridize to any nucleotide sequence along the entire lengthof a nucleic acid molecule provided in Table 1 and/or Table 2.Preferably, a probe of the present invention hybridizes to a region of atarget sequence that encompasses a SNP position indicated in Table 1and/or Table 2. More preferably, a probe hybridizes to a SNP-containingtarget sequence in a sequence-specific manner such that it distinguishesthe target sequence from other nucleotide sequences which vary from thetarget sequence only by which nucleotide is present at the SNP site.Such a probe is particularly useful for detecting the presence of aSNP-containing nucleic acid in a test sample, or for determining whichnucleotide (allele) is present at a particular SNP site (i.e.,genotyping the SNP site).

A nucleic acid hybridization probe may be used for determining thepresence, level, form, and/or distribution of nucleic acid expression.The nucleic acid whose level is determined can be DNA or RNA.Accordingly, probes specific for the SNPs described herein can be usedto assess the presence, expression and/or gene copy number in a givencell, tissue, or organism. These uses are relevant for diagnosis ofdisorders involving an increase or decrease in gene expression relativeto normal levels. In vitro techniques for detection of mRNA include, forexample, Northern blot hybridizations and in situ hybridizations. Invitro techniques for detecting DNA include Southern blot hybridizationsand in situ hybridizations (Sambrook and Russell, 2000, MolecularCloning: A Laboratory Manual, Cold Spring Harbor Press, Cold SpringHarbor, N.Y.).

Probes can be used as part of a diagnostic test kit for identifyingcells or tissues in which a variant protein is expressed, such as bymeasuring the level of a variant protein-encoding nucleic acid (e.g.,mRNA) in a sample of cells from a subject or determining if apolynucleotide contains a SNP of interest.

Thus, the nucleic acid molecules of the invention can be used ashybridization probes to detect the SNPs disclosed herein, therebydetermining whether an individual with the polymorphisms is at risk forpsoriasis and related pathologies or has developed early stagepsoriasis. Detection of a SNP associated with a disease phenotypeprovides a diagnostic tool for an active disease and/or geneticpredisposition to the disease.

Furthermore, the nucleic acid molecules of the invention are thereforeuseful for detecting a gene (gene information is disclosed in Table 2,for example) which contains a SNP disclosed herein and/or products ofsuch genes, such as expressed mRNA transcript molecules (transcriptinformation is disclosed in Table 1, for example), and are thus usefulfor detecting gene expression. The nucleic acid molecules can optionallybe implemented in, for example, an array or kit format for use indetecting gene expression.

The nucleic acid molecules of the invention are also useful as primersto amplify any given region of a nucleic acid molecule, particularly aregion containing a SNP identified in Table 1 and/or Table 2.

The nucleic acid molecules of the invention are also useful forconstructing recombinant vectors (described in greater detail below).Such vectors include expression vectors that express a portion of, orall of, any of the variant peptide sequences provided in Table 1.Vectors also include insertion vectors, used to integrate into anothernucleic acid molecule sequence, such as into the cellular genome, toalter in situ expression of a gene and/or gene product. For example, anendogenous coding sequence can be replaced via homologous recombinationwith all or part of the coding region containing one or morespecifically introduced SNPs.

The nucleic acid molecules of the invention are also useful forexpressing antigenic portions of the variant proteins, particularlyantigenic portions that contain a variant amino acid sequence (e.g., anamino acid substitution) caused by a SNP disclosed in Table 1 and/orTable 2.

The nucleic acid molecules of the invention are also useful forconstructing vectors containing a gene regulatory region of the nucleicacid molecules of the present invention.

The nucleic acid molecules of the invention are also useful fordesigning ribozymes corresponding to all, or a part, of an mRNA moleculeexpressed from a SNP-containing nucleic acid molecule described herein.

The nucleic acid molecules of the invention are also useful forconstructing host cells expressing a part, or all, of the nucleic acidmolecules and variant peptides.

The nucleic acid molecules of the invention are also useful forconstructing transgenic animals expressing all, or a part, of thenucleic acid molecules and variant peptides. The production ofrecombinant cells and transgenic animals having nucleic acid moleculeswhich contain the SNPs disclosed in Table 1 and/or Table 2 allow, forexample, effective clinical design of treatment compounds and dosageregimens.

The nucleic acid molecules of the invention are also useful in assaysfor drug screening to identify compounds that, for example, modulatenucleic acid expression.

The nucleic acid molecules of the invention are also useful in genetherapy in patients whose cells have aberrant gene expression. Thus,recombinant cells, which include a patient's cells that have beenengineered ex vivo and returned to the patient, can be introduced intoan individual where the recombinant cells produce the desired protein totreat the individual.

SNP Genotyping Methods

The process of determining which specific nucleotide (i.e., allele) ispresent at each of one or more SNP positions, such as a SNP position ina nucleic acid molecule disclosed in Table 1 and/or Table 2, is referredto as SNP genotyping. The present invention provides methods of SNPgenotyping, such as for use in screening for psoriasis or relatedpathologies, or determining predisposition thereto, or determiningresponsiveness to a form of treatment, or in genome mapping or SNPassociation analysis, etc.

Nucleic acid samples can be genotyped to determine which allele(s)is/are present at any given genetic region (e.g., SNP position) ofinterest by methods well known in the art. The neighboring sequence canbe used to design SNP detection reagents such as oligonucleotide probes,which may optionally be implemented in a kit format. Exemplary SNPgenotyping methods are described in Chen et al., “Single nucleotidepolymorphism genotyping: biochemistry, protocol, cost and throughput”,Pharmacogenomics J. 2003; 3(2):77-96; Kwok et al., “Detection of singlenucleotide polymorphisms”, Curr Issues Mol Biol. 2003 April; 5(2):43-60;Shi, “Technologies for individual genotyping: detection of geneticpolymorphisms in drug targets and disease genes”, Am J Pharmacogenomics.2002; 2(3):197-205; and Kwok, “Methods for genotyping single nucleotidepolymorphisms”, Annu Rev Genomics Hum Genet 2001; 2:235-58. Exemplarytechniques for high-throughput SNP genotyping are described inMarnellos, “High-throughput SNP analysis for genetic associationstudies”, Curr Opin Drug Discov Devel. 2003 May; 6(3):317-21. Common SNPgenotyping methods include, but are not limited to, TaqMan assays,molecular beacon assays, nucleic acid arrays, allele-specific primerextension, allele-specific PCR, arrayed primer extension, homogeneousprimer extension assays, primer extension with detection by massspectrometry, pyrosequencing, multiplex primer extension sorted ongenetic arrays, ligation with rolling circle amplification, homogeneousligation, OLA (U.S. Pat. No. 4,988,167), multiplex ligation reactionsorted on genetic arrays, restriction-fragment length polymorphism,single base extension-tag assays, and the Invader assay. Such methodsmay be used in combination with detection mechanisms such as, forexample, luminescence or chemiluminescence detection, fluorescencedetection, time-resolved fluorescence detection, fluorescence resonanceenergy transfer, fluorescence polarization, mass spectrometry, andelectrical detection.

Various methods for detecting polymorphisms include, but are not limitedto, methods in which protection from cleavage agents is used to detectmismatched bases in RNA/RNA or RNA/DNA duplexes (Myers et al., Science230:1242 (1985); Cotton et al., PNAS 85:4397 (1988); and Saleeba et al.,Meth. Enzymol. 217:286-295 (1992)), comparison of the electrophoreticmobility of variant and wild type nucleic acid molecules (Orita et al.,PNAS 86:2766 (1989); Cotton et al., Mutat. Res. 285:125-144 (1993); andHayashi et al., Genet. Anal. Tech. Appl. 9:73-79 (1992)), and assayingthe movement of polymorphic or wild-type fragments in polyacrylamidegels containing a gradient of denaturant using denaturing gradient gelelectrophoresis (DGGE) (Myers et al., Nature 313:495 (1985)). Sequencevariations at specific locations can also be assessed by nucleaseprotection assays such as RNase and 51 protection or chemical cleavagemethods.

In a preferred embodiment, SNP genotyping is performed using the TaqManassay, which is also known as the 5′ nuclease assay (U.S. Pat. Nos.5,210,015 and 5,538,848). The TaqMan assay detects the accumulation of aspecific amplified product during PCR. The TaqMan assay utilizes anoligonucleotide probe labeled with a fluorescent reporter dye and aquencher dye. The reporter dye is excited by irradiation at anappropriate wavelength, it transfers energy to the quencher dye in thesame probe via a process called fluorescence resonance energy transfer(FRET). When attached to the probe, the excited reporter dye does notemit a signal. The proximity of the quencher dye to the reporter dye inthe intact probe maintains a reduced fluorescence for the reporter. Thereporter dye and quencher dye may be at the 5′ most and the 3′ mostends, respectively, or vice versa. Alternatively, the reporter dye maybe at the 5′ or 3′ most end while the quencher dye is attached to aninternal nucleotide, or vice versa. In yet another embodiment, both thereporter and the quencher may be attached to internal nucleotides at adistance from each other such that fluorescence of the reporter isreduced.

During PCR, the 5′ nuclease activity of DNA polymerase cleaves theprobe, thereby separating the reporter dye and the quencher dye andresulting in increased fluorescence of the reporter. Accumulation of PCRproduct is detected directly by monitoring the increase in fluorescenceof the reporter dye. The DNA polymerase cleaves the probe between thereporter dye and the quencher dye only if the probe hybridizes to thetarget SNP-containing template which is amplified during PCR, and theprobe is designed to hybridize to the target SNP site only if aparticular SNP allele is present.

Preferred TaqMan primer and probe sequences can readily be determinedusing the SNP and associated nucleic acid sequence information providedherein. A number of computer programs, such as Primer Express (AppliedBiosystems, Foster City, Calif.), can be used to rapidly obtain optimalprimer/probe sets. It will be apparent to one of skill in the art thatsuch primers and probes for detecting the SNPs of the present inventionare useful in diagnostic assays for psoriasis and related pathologies,and can be readily incorporated into a kit format. The present inventionalso includes modifications of the Taqman assay well known in the artsuch as the use of Molecular Beacon probes (U.S. Pat. Nos. 5,118,801 and5,312,728) and other variant formats (U.S. Pat. Nos. 5,866,336 and6,117,635).

Another preferred method for genotyping the SNPs of the presentinvention is the use of two oligonucleotide probes in an OLA (see, e.g.,U.S. Pat. No. 4,988,617). In this method, one probe hybridizes to asegment of a target nucleic acid with its 3′ most end aligned with theSNP site. A second probe hybridizes to an adjacent segment of the targetnucleic acid molecule directly 3′ to the first probe. The two juxtaposedprobes hybridize to the target nucleic acid molecule, and are ligated inthe presence of a linking agent such as a ligase if there is perfectcomplementarity between the 3′ most nucleotide of the first probe withthe SNP site. If there is a mismatch, ligation would not occur. Afterthe reaction, the ligated probes are separated from the target nucleicacid molecule, and detected as indicators of the presence of a SNP.

The following patents, patent applications, and published internationalpatent applications, which are all hereby incorporated by reference,provide additional information pertaining to techniques for carrying outvarious types of OLA: U.S. Pat. Nos. 6,027,889, 6,268,148, 5,494,810,5,830,711, and 6,054,564 describe OLA strategies for performing SNPdetection; WO 97/31256 and WO 00/56927 describe OLA strategies forperforming SNP detection using universal arrays, wherein a zipcodesequence can be introduced into one of the hybridization probes, and theresulting product, or amplified product, hybridized to a universal zipcode array; U.S. application US01/17329 (and Ser. No. 09/584,905)describes OLA (or LDR) followed by PCR, wherein zipcodes areincorporated into OLA probes, and amplified PCR products are determinedby electrophoretic or universal zipcode array readout; U.S. applications60/427,818, 60/445,636, and 60/445,494 describe SNPlex methods andsoftware for multiplexed SNP detection using OLA followed by PCR,wherein zipcodes are incorporated into OLA probes, and amplified PCRproducts are hybridized with a zipchute reagent, and the identity of theSNP determined from electrophoretic readout of the zipchute. In someembodiments, OLA is carried out prior to PCR (or another method ofnucleic acid amplification). In other embodiments, PCR (or anothermethod of nucleic acid amplification) is carried out prior to OLA.

Another method for SNP genotyping is based on mass spectrometry. Massspectrometry takes advantage of the unique mass of each of the fournucleotides of DNA. SNPs can be unambiguously genotyped by massspectrometry by measuring the differences in the mass of nucleic acidshaving alternative SNP alleles. MALDI-TOF (Matrix Assisted LaserDesorption Ionization-Time of Flight) mass spectrometry technology ispreferred for extremely precise determinations of molecular mass, suchas SNPs. Numerous approaches to SNP analysis have been developed basedon mass spectrometry. Preferred mass spectrometry-based methods of SNPgenotyping include primer extension assays, which can also be utilizedin combination with other approaches, such as traditional gel-basedformats and microarrays.

Typically, the primer extension assay involves designing and annealing aprimer to a template PCR amplicon upstream (5′) from a target SNPposition. A mix of dideoxynucleotide triphosphates (ddNTPs) and/ordeoxynucleotide triphosphates (dNTPs) are added to a reaction mixturecontaining template (e.g., a SNP-containing nucleic acid molecule whichhas typically been amplified, such as by PCR), primer, and DNApolymerase. Extension of the primer terminates at the first position inthe template where a nucleotide complementary to one of the ddNTPs inthe mix occurs. The primer can be either immediately adjacent (i.e., thenucleotide at the 3′ end of the primer hybridizes to the nucleotide nextto the target SNP site) or two or more nucleotides removed from the SNPposition. If the primer is several nucleotides removed from the targetSNP position, the only limitation is that the template sequence betweenthe 3′ end of the primer and the SNP position cannot contain anucleotide of the same type as the one to be detected, or this willcause premature termination of the extension primer. Alternatively, ifall four ddNTPs alone, with no dNTPs, are added to the reaction mixture,the primer will always be extended by only one nucleotide, correspondingto the target SNP position. In this instance, primers are designed tobind one nucleotide upstream from the SNP position (i.e., the nucleotideat the 3′ end of the primer hybridizes to the nucleotide that isimmediately adjacent to the target SNP site on the 5′ side of the targetSNP site). Extension by only one nucleotide is preferable, as itminimizes the overall mass of the extended primer, thereby increasingthe resolution of mass differences between alternative SNP nucleotides.Furthermore, mass-tagged ddNTPs can be employed in the primer extensionreactions in place of unmodified ddNTPs. This increases the massdifference between primers extended with these ddNTPs, thereby providingincreased sensitivity and accuracy, and is particularly useful fortyping heterozygous base positions. Mass-tagging also alleviates theneed for intensive sample-preparation procedures and decreases thenecessary resolving power of the mass spectrometer.

The extended primers can then be purified and analyzed by MALDI-TOF massspectrometry to determine the identity of the nucleotide present at thetarget SNP position. In one method of analysis, the products from theprimer extension reaction are combined with light absorbing crystalsthat form a matrix. The matrix is then hit with an energy source such asa laser to ionize and desorb the nucleic acid molecules into thegas-phase. The ionized molecules are then ejected into a flight tube andaccelerated down the tube towards a detector. The time between theionization event, such as a laser pulse, and collision of the moleculewith the detector is the time of flight of that molecule. The time offlight is precisely correlated with the mass-to-charge ratio (m/z) ofthe ionized molecule. Ions with smaller m/z travel down the tube fasterthan ions with larger m/z and therefore the lighter ions reach thedetector before the heavier ions. The time-of-flight is then convertedinto a corresponding, and highly precise, m/z. In this manner, SNPs canbe identified based on the slight differences in mass, and thecorresponding time of flight differences, inherent in nucleic acidmolecules having different nucleotides at a single base position. Forfurther information regarding the use of primer extension assays inconjunction with MALDI-TOF mass spectrometry for SNP genotyping, see,e.g., Wise et al., “A standard protocol for single nucleotide primerextension in the human genome using matrix-assisted laserdesorption/ionization time-of-flight mass spectrometry”, Rapid CommunMass Spectrom. 2003; 17(11):1195-202.

The following references provide further information describing massspectrometry-based methods for SNP genotyping: Bocker, “SNP and mutationdiscovery using base-specific cleavage and MALDI-TOF mass spectrometry”,Bioinformatics. 2003 July; 19 Suppl 1:144-153; Storm et al., “MALDI-TOFmass spectrometry-based SNP genotyping”, Methods Mol Biol. 2003;212:241-62; Jurinke et al., “The use of Mass ARRAY technology for highthroughput genotyping”, Adv Biochem Eng Biotechnol. 2002; 77:57-74; andJurinke et al., “Automated genotyping using the DNA MassArraytechnology”, Methods Mol Biol. 2002; 187:179-92.

SNPs can also be scored by direct DNA sequencing. A variety of automatedsequencing procedures can be utilized ((1995) Biotechniques 19:448),including sequencing by mass spectrometry (see, e.g., PCT InternationalPublication No. WO94/16101; Cohen et al., Adv. Chromatogr. 36:127-162(1996); and Griffin et al., Appl. Biochem. Biotechnol. 38:147-159(1993)). The nucleic acid sequences of the present invention enable oneof ordinary skill in the art to readily design sequencing primers forsuch automated sequencing procedures. Commercial instrumentation, suchas the Applied Biosystems 377, 3100, 3700, 3730, and 3730×1 DNAAnalyzers (Foster City, Calif.), is commonly used in the art forautomated sequencing.

Other methods that can be used to genotype the SNPs of the presentinvention include single-strand conformational polymorphism (SSCP), anddenaturing gradient gel electrophoresis (DGGE) (Myers et al., Nature313:495 (1985)). SSCP identifies base differences by alteration inelectrophoretic migration of single stranded PCR products, as describedin Orita et al., Proc. Nat. Acad. Single-stranded PCR products can begenerated by heating or otherwise denaturing double stranded PCRproducts. Single-stranded nucleic acids may refold or form secondarystructures that are partially dependent on the base sequence. Thedifferent electrophoretic mobilities of single-stranded amplificationproducts are related to base-sequence differences at SNP positions. DGGEdifferentiates SNP alleles based on the different sequence-dependentstabilities and melting properties inherent in polymorphic DNA and thecorresponding differences in electrophoretic migration patterns in adenaturing gradient gel (Erlich, ed., PCR Technology, Principles andApplications for DNA Amplification, W.H. Freeman and Co, New York, 1992,Chapter 7).

Sequence-specific ribozymes (U.S. Pat. No. 5,498,531) can also be usedto score SNPs based on the development or loss of a ribozyme cleavagesite. Perfectly matched sequences can be distinguished from mismatchedsequences by nuclease cleavage digestion assays or by differences inmelting temperature. If the SNP affects a restriction enzyme cleavagesite, the SNP can be identified by alterations in restriction enzymedigestion patterns, and the corresponding changes in nucleic acidfragment lengths determined by gel electrophoresis

SNP genotyping can include the steps of, for example, collecting abiological sample from a human subject (e.g., sample of tissues, cells,fluids, secretions, etc.), isolating nucleic acids (e.g., genomic DNA,mRNA or both) from the cells of the sample, contacting the nucleic acidswith one or more primers which specifically hybridize to a region of theisolated nucleic acid containing a target SNP under conditions such thathybridization and amplification of the target nucleic acid regionoccurs, and determining the nucleotide present at the SNP position ofinterest, or, in some assays, detecting the presence or absence of anamplification product (assays can be designed so that hybridizationand/or amplification will only occur if a particular SNP allele ispresent or absent). In some assays, the size of the amplificationproduct is detected and compared to the length of a control sample; forexample, deletions and insertions can be detected by a change in size ofthe amplified product compared to a normal genotype.

SNP genotyping is useful for numerous practical applications, asdescribed below. Examples of such applications include, but are notlimited to, SNP-disease association analysis, disease predispositionscreening, disease diagnosis, disease prognosis, disease progressionmonitoring, determining therapeutic strategies based on an individual'sgenotype (“pharmacogenomics”), developing therapeutic agents based onSNP genotypes associated with a disease or likelihood of responding to adrug, stratifying a patient population for clinical trial for atreatment regimen, predicting the likelihood that an individual willexperience toxic side effects from a therapeutic agent, and humanidentification applications such as forensics.

Analysis of Genetic Association Between SNPs and Phenotypic Traits

SNP genotyping for disease diagnosis, disease predisposition screening,disease prognosis, determining drug responsiveness (pharmacogenomics),drug toxicity screening, and other uses described herein, typicallyrelies on initially establishing a genetic association between one ormore specific SNPs and the particular phenotypic traits of interest.

Different study designs may be used for genetic association studies(Modern Epidemiology, Lippincott Williams & Wilkins (1998), 609-622).Observational studies are most frequently carried out in which theresponse of the patients is not interfered with. The first type ofobservational study identifies a sample of persons in whom the suspectedcause of the disease is present and another sample of persons in whomthe suspected cause is absent, and then the frequency of development ofdisease in the two samples is compared. These sampled populations arecalled cohorts, and the study is a prospective study. The other type ofobservational study is case-control or a retrospective study. In typicalcase-control studies, samples are collected from individuals with thephenotype of interest (cases) such as certain manifestations of adisease, and from individuals without the phenotype (controls) in apopulation (target population) that conclusions are to be drawn from.Then the possible causes of the disease are investigatedretrospectively. As the time and costs of collecting samples incase-control studies are considerably less than those for prospectivestudies, case-control studies are the more commonly used study design ingenetic association studies, at least during the exploration anddiscovery stage.

In both types of observational studies, there may be potentialconfounding factors that should be taken into consideration. Confoundingfactors are those that are associated with both the real cause(s) of thedisease and the disease itself, and they include demographic informationsuch as age, gender, ethnicity as well as environmental factors. Whenconfounding factors are not matched in cases and controls in a study,and are not controlled properly, spurious association results can arise.If potential confounding factors are identified, they should becontrolled for by analysis methods explained below.

In a genetic association study, the cause of interest to be tested is acertain allele or a SNP or a combination of alleles or a haplotype fromseveral SNPs. Thus, tissue specimens (e.g., whole blood) from thesampled individuals may be collected and genomic DNA genotyped for theSNP(s) of interest. In addition to the phenotypic trait of interest,other information such as demographic (e.g., age, gender, ethnicity,etc.), clinical, and environmental information that may influence theoutcome of the trait can be collected to further characterize and definethe sample set. In many cases, these factors are known to be associatedwith diseases and/or SNP allele frequencies. There are likelygene-environment and/or gene-gene interactions as well. Analysis methodsto address gene-environment and gene-gene interactions (for example, theeffects of the presence of both susceptibility alleles at two differentgenes can be greater than the effects of the individual alleles at twogenes combined) are discussed below.

After all the relevant phenotypic and genotypic information has beenobtained, statistical analyses are carried out to determine if there isany significant correlation between the presence of an allele or agenotype with the phenotypic characteristics of an individual.Preferably, data inspection and cleaning are first performed beforecarrying out statistical tests for genetic association. Epidemiologicaland clinical data of the samples can be summarized by descriptivestatistics with tables and graphs. Data validation is preferablyperformed to check for data completion, inconsistent entries, andoutliers. Chi-squared tests and t-tests (Wilcoxon rank-sum tests ifdistributions are not normal) may then be used to check for significantdifferences between cases and controls for discrete and continuousvariables, respectively. To ensure genotyping quality, Hardy-Weinbergdisequilibrium tests can be performed on cases and controls separately.Significant deviation from Hardy-Weinberg equilibrium (HWE) in bothcases and controls for individual markers can be indicative ofgenotyping errors. If HWE is violated in a majority of markers, it isindicative of population substructure that should be furtherinvestigated. Moreover, Hardy-Weinberg disequilibrium in cases only canindicate genetic association of the markers with the disease (GeneticData Analysis, Weir B., Sinauer (1990)).

To test whether an allele of a single SNP is associated with the case orcontrol status of a phenotypic trait, one skilled in the art can compareallele frequencies in cases and controls. Standard chi-squared tests andFisher exact tests can be carried out on a 2×2 table (2 SNP alleles×2outcomes in the categorical trait of interest). To test whethergenotypes of a SNP are associated, chi-squared tests can be carried outon a 3×2 table (3 genotypes×2 outcomes). Score tests are also carriedout for genotypic association to contrast the three genotypicfrequencies (major homozygotes, heterozygotes and minor homozygotes) incases and controls, and to look for trends using 3 different modes ofinheritance, namely dominant (with contrast coefficients 2, −1, −1),additive (with contrast coefficients 1, 0, −1) and recessive (withcontrast coefficients 1, 1, −2). Odds ratios for minor versus majoralleles, and odds ratios for heterozygote and homozygote variants versusthe wild type genotypes are calculated with the desired confidencelimits, usually 95%.

In order to control for confounders and to test for interaction andeffect modifiers, stratified analyses may be performed using stratifiedfactors that are likely to be confounding, including demographicinformation such as age, ethnicity, and gender, or an interactingelement or effect modifier, such as a known major gene (e.g., APOE forAlzheimer's disease or HLA genes for autoimmune diseases), orenvironmental factors such as smoking in lung cancer. Stratifiedassociation tests may be carried out using Cochran-Mantel-Haenszel teststhat take into account the ordinal nature of genotypes with 0, 1, and 2variant alleles. Exact tests by StatXact may also be performed whencomputationally possible. Another way to adjust for confounding effectsand test for interactions is to perform stepwise multiple logisticregression analysis using statistical packages such as SAS or R.Logistic regression is a model-building technique in which the bestfitting and most parsimonious model is built to describe the relationbetween the dichotomous outcome (for instance, getting a certain diseaseor not) and a set of independent variables (for instance, genotypes ofdifferent associated genes, and the associated demographic andenvironmental factors). The most common model is one in which the logittransformation of the odds ratios is expressed as a linear combinationof the variables (main effects) and their cross-product terms(interactions) (Applied Logistic Regression, Hosmer and Lemeshow, Wiley(2000)). To test whether a certain variable or interaction issignificantly associated with the outcome, coefficients in the model arefirst estimated and then tested for statistical significance of theirdeparture from zero.

In addition to performing association tests one marker at a time,haplotype association analysis may also be performed to study a numberof markers that are closely linked together. Haplotype association testscan have better power than genotypic or allelic association tests whenthe tested markers are not the disease-causing mutations themselves butare in linkage disequilibrium with such mutations. The test will even bemore powerful if the disease is indeed caused by a combination ofalleles on a haplotype (e.g., APOE is a haplotype formed by 2 SNPs thatare very close to each other). In order to perform haplotype associationeffectively, marker-marker linkage disequilibrium measures, both D′ andR², are typically calculated for the markers within a gene to elucidatethe haplotype structure. Recent studies (Daly et al, Nature Genetics,29, 232-235, 2001) in linkage disequilibrium indicate that SNPs within agene are organized in block pattern, and a high degree of linkagedisequilibrium exists within blocks and very little linkagedisequilibrium exists between blocks. Haplotype association with thedisease status can be performed using such blocks once they have beenelucidated.

Haplotype association tests can be carried out in a similar fashion asthe allelic and genotypic association tests. Each haplotype in a gene isanalogous to an allele in a multi-allelic marker. One skilled in the artcan either compare the haplotype frequencies in cases and controls ortest genetic association with different pairs of haplotypes. It has beenproposed (Schaid et al, Am. J. Hum. Genet., 70, 425-434, 2002) thatscore tests can be done on haplotypes using the program “haplo.score”.In that method, haplotypes are first inferred by EM algorithm and scoretests are carried out with a generalized linear model (GLM) frameworkthat allows the adjustment of other factors.

An important decision in the performance of genetic association tests isthe determination of the significance level at which significantassociation can be declared when the p-value of the tests reaches thatlevel. In an exploratory analysis where positive hits will be followedup in subsequent confirmatory testing, an unadjusted p-value <0.2 (asignificance level on the lenient side), for example, may be used forgenerating hypotheses for significant association of a SNP with certainphenotypic characteristics of a disease. It is preferred that a p-value<0.05 (a significance level traditionally used in the art) is achievedin order for a SNP to be considered to have an association with adisease. It is more preferred that a p-value <0.01 (a significance levelon the stringent side) is achieved for an association to be declared.When hits are followed up in confirmatory analyses in more samples ofthe same source or in different samples from different sources,adjustment for multiple testing will be performed as to avoid excessnumber of hits while maintaining the experiment-wise error rates at0.05. While there are different methods to adjust for multiple testingto control for different kinds of error rates, a commonly used butrather conservative method is Bonferroni correction to control theexperiment-wise or family-wise error rate (Multiple comparisons andmultiple tests, Westfall et al, SAS Institute (1999)). Permutation teststo control for the false discovery rates, FDR, can be more powerful(Benjamini and Hochberg, Journal of the Royal Statistical Society,Series B 57, 1289-1300, 1995, Resampling-based Multiple Testing,Westfall and Young, Wiley (1993)). Such methods to control formultiplicity would be preferred when the tests are dependent andcontrolling for false discovery rates is sufficient as opposed tocontrolling for the experiment-wise error rates.

In replication studies using samples from different populations afterstatistically significant markers have been identified in theexploratory stage, meta-analyses can then be performed by combiningevidence of different studies (Modern Epidemiology, Lippincott Williams& Wilkins, 1998, 643-673). If available, association results known inthe art for the same SNPs can be included in the meta-analyses.

Since both genotyping and disease status classification can involveerrors, sensitivity analyses may be performed to see how odds ratios andp-values would change upon various estimates on genotyping and diseaseclassification error rates.

It has been well known that subpopulation-based sampling bias betweencases and controls can lead to spurious results in case-controlassociation studies (Ewens and Spielman, Am. J. Hum. Genet. 62, 450-458,1995) when prevalence of the disease is associated with differentsubpopulation groups. Such bias can also lead to a loss of statisticalpower in genetic association studies. To detect populationstratification, Pritchard and Rosenberg (Pritchard et al. Am. J. Hum.Gen. 1999, 65:220-228) suggested typing markers that are unlinked to thedisease and using results of association tests on those markers todetermine whether there is any population stratification. Whenstratification is detected, the genomic control (GC) method as proposedby Devlin and Roeder (Devlin et al. Biometrics 1999, 55:997-1004) can beused to adjust for the inflation of test statistics due to populationstratification. GC method is robust to changes in population structurelevels as well as being applicable to DNA pooling designs (Devlin et al.Genet. Epidem. 20001, 21:273-284).

While Pritchard's method recommended using 15-20 unlinked microsatellitemarkers, it suggested using more than 30 biallelic markers to get enoughpower to detect population stratification. For the GC method, it hasbeen shown (Bacanu et al. Am. J. Hum. Genet. 2000, 66:1933-1944) thatabout 60-70 biallelic markers are sufficient to estimate the inflationfactor for the test statistics due to population stratification. Hence,70 intergenic SNPs can be chosen in unlinked regions as indicated in agenome scan (Kehoe et al. Hum. Mol. Genet. 1999, 8:237-245).

Once individual risk factors, genetic or non-genetic, have been foundfor the predisposition to disease, the next step is to set up aclassification/prediction scheme to predict the category (for instance,disease or no-disease) that an individual will be in depending on hisgenotypes of associated SNPs and other non-genetic risk factors.Logistic regression for discrete trait and linear regression forcontinuous trait are standard techniques for such tasks (AppliedRegression Analysis, Draper and Smith, Wiley (1998)). Moreover, othertechniques can also be used for setting up classification. Suchtechniques include, but are not limited to, MART, CART, neural network,and discriminant analyses that are suitable for use in comparing theperformance of different methods (The Elements of Statistical Learning,Hastie, Tibshirani & Friedman, Springer (2002)).

Disease Diagnosis and Predisposition Screening

Information on association/correlation between genotypes anddisease-related phenotypes can be exploited in several ways. Forexample, in the case of a highly statistically significant associationbetween one or more SNPs with predisposition to a disease for whichtreatment is available, detection of such a genotype pattern in anindividual may justify immediate administration of treatment, or atleast the institution of regular monitoring of the individual. Detectionof the susceptibility alleles associated with serious disease in acouple contemplating having children may also be valuable to the couplein their reproductive decisions. In the case of a weaker but stillstatistically significant association between a SNP and a human disease,immediate therapeutic intervention or monitoring may not be justifiedafter detecting the susceptibility allele or SNP. Nevertheless, thesubject can be motivated to begin simple life-style changes (e.g., diet,exercise) that can be accomplished at little or no cost to theindividual but would confer potential benefits in reducing the risk ofdeveloping conditions for which that individual may have an increasedrisk by virtue of having the susceptibility allele(s).

The SNPs of the invention may contribute to psoriasis and relatedpathologies in an individual in different ways. Some polymorphisms occurwithin a protein coding sequence and contribute to disease phenotype byaffecting protein structure. Other polymorphisms occur in noncodingregions but may exert phenotypic effects indirectly via influence on,for example, replication, transcription, and/or translation. A singleSNP may affect more than one phenotypic trait. Likewise, a singlephenotypic trait may be affected by multiple SNPs in different genes.

As used herein, the terms “diagnose”, “diagnosis”, and “diagnostics”include, but are not limited to any of the following: detection ofpsoriasis that an individual may presently have,predisposition/susceptibility screening (i.e., determining the increasedrisk of an individual in developing psoriasis in the future, ordetermining whether an individual has a decreased risk of developingpsoriasis in the future, determining a particular type or subclass ofpsoriasis in an individual known to have psoriasis, confirming orreinforcing a previously made diagnosis of psoriasis, pharmacogenomicevaluation of an individual to determine which therapeutic strategy thatindividual is most likely to positively respond to or to predict whethera patient is likely to respond to a particular treatment, predictingwhether a patient is likely to experience toxic effects from aparticular treatment or therapeutic compound, and evaluating the futureprognosis of an individual having psoriasis. Such diagnostic uses arebased on the SNPs individually or in a unique combination or SNPhaplotypes of the present invention.

Haplotypes are particularly useful in that, for example, fewer SNPs canbe genotyped to determine if a particular genomic region harbors a locusthat influences a particular phenotype, such as in linkagedisequilibrium-based SNP association analysis.

Linkage disequilibrium (LD) refers to the co-inheritance of alleles(e.g., alternative nucleotides) at two or more different SNP sites atfrequencies greater than would be expected from the separate frequenciesof occurrence of each allele in a given population. The expectedfrequency of co-occurrence of two alleles that are inheritedindependently is the frequency of the first allele multiplied by thefrequency of the second allele. Alleles that co-occur at expectedfrequencies are said to be in “linkage equilibrium”. In contrast, LDrefers to any non-random genetic association between allele(s) at two ormore different SNP sites, which is generally due to the physicalproximity of the two loci along a chromosome. LD can occur when two ormore SNPs sites are in close physical proximity to each other on a givenchromosome and therefore alleles at these SNP sites will tend to remainunseparated for multiple generations with the consequence that aparticular nucleotide (allele) at one SNP site will show a non-randomassociation with a particular nucleotide (allele) at a different SNPsite located nearby. Hence, genotyping one of the SNP sites will givealmost the same information as genotyping the other SNP site that is inLD.

Various degrees of LD can be encountered between two or more SNPs withthe result being that some SNPs are more closely associated (i.e., instronger LD) than others. Furthermore, the physical distance over whichLD extends along a chromosome differs between different regions of thegenome, and therefore the degree of physical separation between two ormore SNP sites necessary for LD to occur can differ between differentregions of the genome.

For diagnostic purposes and similar uses, if a particular SNP site isfound to be useful for diagnosing psoriasis and related pathologies(e.g., has a significant statistical association with the conditionand/or is recognized as a causative polymorphism for the condition),then the skilled artisan would recognize that other SNP sites which arein LD with this SNP site would also be useful for diagnosing thecondition. Thus, polymorphisms (e.g., SNPs and/or haplotypes) that arenot the actual disease-causing (causative) polymorphisms, but are in LDwith such causative polymorphisms, are also useful. In such instances,the genotype of the polymorphism(s) that is/are in LD with the causativepolymorphism is predictive of the genotype of the causative polymorphismand, consequently, predictive of the phenotype (e.g., psoriasis) that isinfluenced by the causative SNP(s). Therefore, polymorphic markers thatare in LD with causative polymorphisms are useful as diagnostic markers,and are particularly useful when the actual causative polymorphism(s)is/are unknown.

Examples of polymorphisms that can be in LD with one or more causativepolymorphisms (and/or in LD with one or more polymorphisms that have asignificant statistical association with a condition) and thereforeuseful for diagnosing the same condition that the causative/associatedSNP(s) is used to diagnose, include, for example, other SNPs in the samegene, protein-coding, or mRNA transcript-coding region as thecausative/associated SNP, other SNPs in the same exon or same intron asthe causative/associated SNP, other SNPs in the same haplotype block asthe causative/associated SNP, other SNPs in the same intergenic regionas the causative/associated SNP, SNPs that are outside but near a gene(e.g., within 6 kb on either side, 5′ or 3′, of a gene boundary) thatharbors a causative/associated SNP, etc. Such useful LD SNPs can beselected from among the SNPs disclosed in Tables 1-4, for example.

Linkage disequilibrium in the human genome is reviewed in the followingreferences: Wall et al. et al., “Haplotype blocks and linkagedisequilibrium in the human genome,”, Nat Rev Genet. 2003 August;4(8):587-97 (August 2003); Garner et al.et al., “On selecting markersfor association studies: patterns of linkage disequilibrium between twoand three diallelic loci,”, Genet Epidemiol. 2003 January; 24(1):57-67(January 2003); Ardlie et al.et al., “Patterns of linkage disequilibriumin the human genome,”, Nat Rev Genet. 2002 April; 3(4):299-309 (April2002); (erratum in Nat Rev Genet 2002 July; 3(7):566 (July 2002); andRemm et al.et al., “High-density genotyping and linkage disequilibriumin the human genome using chromosome 22 as a model,”; Curr Opin ChemBiol. 2002 February; 6(1):24-30 (February 2002); J. B. S. Haldane, “JBS(1919) The combination of linkage values, and the calculation ofdistances between the loci of linked factors,”. J Genet 8:299-309(1919); G. Mendel, G. (1866) Versuche über Pflanzen-Hybriden.Verhandlungen des naturforschenden Vereines in Brünn [(Proceedings ofthe Natural History Society of Brünn)] (1866); Lewin B (1990) Genes IV,B. Lewin, ed., Oxford University Press, N.Y. New York, USA (1990); D. L.Hartl D L and A. G. Clark A G (1989) Principles of Population Genetics2^(nd) ed., Sinauer Associates, Inc., Ma Sunderland, Mass., USA (1989);J. H. Gillespie J H (2004) Population Genetics: A Concise Guide. 2^(nd)ed., Johns Hopkins University Press. (2004) USA; R. C. Lewontin, “R C(1964) The interaction of selection and linkage. I. Generalconsiderations; heterotic models,”. Genetics 49:49-67 (1964); P. G.Hoel, P G (1954) Introduction to Mathematical Statistics 2^(nd) ed.,John Wiley & Sons, Inc., N.Y. New York, USA (1954); R. R. Hudson, R R“(2001) Two-locus sampling distributions and their application,”.Genetics 159:1805-1817 (2001); A. P. Dempster A P, N. M. Laird, D. B. NM, Rubin, “D B (1977) Maximum likelihood from incomplete data via the EMalgorithm,”. JR Stat Soc 39:1-48 (1977); L. Excoffier L, M. Slatkin, M“(1995) Maximum-likelihood estimation of molecular haplotype frequenciesin a diploid population,”. Mol Biol Evol 12(5):921-927 (1995); D. A.Tregouet D A, S. Escolano S, L. Tiret L, A. Mallet A, J. L. Golmard, J L“(2004) A new algorithm for haplotype-based association analysis: theStochastic-EM algorithm,”. Ann Hum Genet 68(Pt 2):165-177 (2004); A. D.Long A D and C. H. Langley C H, “(1999) The power of association studiesto detect the contribution of candidate genetic loci to variation incomplex traits,”. Genome Research 9:720-731 (1999); A. Agresti, A (1990)Categorical Data Analysis, John Wiley & Sons, Inc., N.Y. New York, USA(1990); K. Lange, K (1997) Mathematical and Statistical Methods forGenetic Analysis, Springer-Verlag New York, Inc., N.Y. New York, USA(1997); The International HapMap Consortium, “(2003) The InternationalHapMap Project,”. Nature 426:789-796 (2003); The International HapMapConsortium, “(2005) A haplotype map of the human genome,”. Nature437:1299-1320 (2005); G. A. Thorisson G A, A. V. Smith A V, L. KrishnanL, L. D. Stein L D (2005), “The International HapMap Project Web Site,”.Genome Research 15:1591-1593 (2005); G. McVean, C. C. A. G, Spencer C CA, R. Chaix R (2005), “Perspectives on human genetic variation from theHapMap project,”. PLoS Genetics 1(4):413-418 (2005); J. N. Hirschhorn JN, M. J. Daly, M J “(2005) Genome-wide association studies for commondiseases and complex traits,”. Nat Genet 6:95-108 (2005); S. J. Schrodi,“S J (2005) A probabilistic approach to large-scale association scans: asemi-Bayesian method to detect disease-predisposing alleles,”. SAGMB4(1):31 (2005); W. Y. S. Wang W Y S, B. J. Barratt B J, D. G. Clayton DG, J. A. Todd, “J A (2005) Genome-wide association studies: theoreticaland practical concerns,”. Nat Rev Genet 6:109-118 (2005); J. K.Pritchard J K, M. Przeworski, “M (2001) Linkage disequilibrium inhumans: models and data,”. Am J Hum Genet 69:1-14 (2001).

As discussed above, one aspect of the present invention is the discoverythat SNPs which are in certain LD distance with the interrogated SNP canalso be used as valid markers for identifying an increased or decreasedrisks of having or developing psoriasis. As used herein, the term“interrogated SNP” refers to SNPs that have been found to be associatedwith an increased or decreased risk of disease using genotyping resultsand analysis, or other appropriate experimental method as exemplified inthe working examples described in this application. As used herein, theterm “LD SNP” refers to a SNP that has been characterized as a SNPassociating with an increased or decreased risk of diseases due to theirbeing in LD with the “interrogated SNP” under the methods of calculationdescribed in the application. Below, applicants describe the methods ofcalculation with which one of ordinary skilled in the art may determineif a particular SNP is in LD with an interrogated SNP. The parameter r²is commonly used in the genetics art to characterize the extent oflinkage disequilibrium between markers (Hudson, 2001). As used herein,the term “in LD with” refers to a particular SNP that is measured atabove the threshold of a parameter such as r² with an interrogated SNP.

It is now common place to directly observe genetic variants in a sampleof chromosomes obtained from a population. Suppose one has genotype dataat two genetic markers located on the same chromosome, for the markers Aand B. Further suppose that two alleles segregate at each of these twomarkers such that alleles A₁ and A₂ can be found at marker A and allelesB₁ and B₂ at marker B. Also assume that these two markers are on a humanautosome. If one is to examine a specific individual and find that theyare heterozygous at both markers, such that their two-marker genotype isA₁A₂B₁B₂, then there are two possible configurations: the individual inquestion could have the alleles A₁B₁ on one chromosome and A₂B₂ on theremaining chromosome; alternatively, the individual could have allelesA₁B₂ on one chromosome and A₂B₁ on the other. The arrangement of alleleson a chromosome is called a haplotype. In this illustration, theindividual could have haplotypes A₁B₁/A₂B₂ or A₁B₂/A₂B₁ (see Hartl andClark (1989) for a more complete description). The concept of linkageequilibrium relates the frequency of haplotypes to the allelefrequencies.

Assume that a sample of individuals is selected from a largerpopulation. Considering the two markers described above, each having twoalleles, there are four possible haplotypes: A₁B₁, A₁B₂, A₂B₁ and A₂B₂.Denote the frequencies of these four haplotypes with the followingnotation.P ₁₁=freq(A ₁ B ₁)  (1)P ₁₂=freq(A ₁ B ₂)  (2)P ₂₁=freq(A ₂ B ₁)  (3)P ₂₂=freq(A ₂ B ₂)  (4)The allele frequencies at the two markers are then the sum of differenthaplotype frequencies, it is straightforward to write down a similar setof equations relating single-marker allele frequencies to two-markerhaplotype frequencies:p ₁=freq(A ₁)=P ₁₁ +P ₁₂  (5)p ₂=freq(A ₂)=P ₂₁ +P ₂₂  (6)q ₁=freq(B ₁)=P ₁₁ +P ₂₁  (7)q ₂=freq(B ₂)=P ₁₂ +P ₂₂  (8)Note that the four haplotype frequencies and the allele frequencies ateach marker must sum to a frequency of 1.P ₁₁ +P ₁₂ +P ₂₁ +P ₂₂=1  (9)p ₁ +p ₂=1  (10)q ₁ +q ₂=1  (11)If there is no correlation between the alleles at the two markers, onewould expect that the frequency of the haplotypes would be approximatelythe product of the composite alleles. Therefore,P ₁₁ ≈p ₁ q ₁  (12)P ₁₂ ≈p ₁ q ₂  (13)P ₂₁ ≈p ₂ q ₁  (14)P ₂₂ ≈p ₂ q ₂  (15)These approximating equations (12)-(15) represent the concept of linkageequilibrium where there is independent assortment between the twomarkers—the alleles at the two markers occur together at random. Theseare represented as approximations because linkage equilibrium andlinkage disequilibrium are concepts typically thought of as propertiesof a sample of chromosomes; and as such they are susceptible tostochastic fluctuations due to the sampling process. Empirically, manypairs of genetic markers will be in linkage equilibrium, but certainlynot all pairs.

Having established the concept of linkage equilibrium above, applicantscan now describe the concept of linkage disequilibrium (LD), which isthe deviation from linkage equilibrium. Since the frequency of the A₁B₁haplotype is approximately the product of the allele frequencies for A₁and B₁ under the assumption of linkage equilibrium as statedmathematically in (12), a simple measure for the amount of departurefrom linkage equilibrium is the difference in these two quantities, D,D=P ₁₁ −p ₁ q ₁  (16)D=0 indicates perfect linkage equilibrium. Substantial departures fromD=0 indicates LD in the sample of chromosomes examined. Many propertiesof D are discussed in Lewontin (1964) including the maximum and minimumvalues that D can take. Mathematically, using basic algebra, it can beshown that D can also be written solely in terms of haplotypes:D=P ₁₁ P ₂₂ −P ₁₂ P ₂₁  (17)If one transforms D by squaring it and subsequently dividing by theproduct of the allele frequencies of A₁, A₂, B₁ and B₂, the resultingquantity, called r², is equivalent to the square of the Pearson'scorrelation coefficient commonly used in statistics (e.g. Hoel, 1954).

$\begin{matrix}{r^{2} = \frac{D^{2}}{p_{1}p_{2}q_{1}q_{2}}} & (18)\end{matrix}$

As with D, values of r² close to 0 indicate linkage equilibrium betweenthe two markers examined in the sample set. As values of r² increase,the two markers are said to be in linkage disequilibrium. The range ofvalues that r² can take are from 0 to 1. r²=1 when there is a perfectcorrelation between the alleles at the two markers.

In addition, the quantities discussed above are sample-specific. And assuch, it is necessary to formulate notation specific to the samplesstudied. In the approach discussed here, three types of samples are ofprimary interest: (i) a sample of chromosomes from individuals affectedby a disease-related phenotype (cases), (ii) a sample of chromosomesobtained from individuals not affected by the disease-related phenotype(controls), and (iii) a standard sample set used for the construction ofhaplotypes and calculation pairwise linkage disequilibrium. For theallele frequencies used in the development of the method describedbelow, an additional subscript will be added to denote either the caseor control sample sets.p _(1,cs)=freq(A ₁ in cases)  (19)p _(2,cs)=freq(A ₂ in cases)  (20)q _(1,cs)=freq(B ₁ in cases)  (21)q _(2,cs)=freq(B ₂ in cases)  (22)Similarly,p _(1,ct)=freq(A ₁ in controls)  (23)p _(2,ct)=freq(A ₂ in controls)  (24)q _(1,ct)=freq(B ₁ in controls)  (25)q _(2,ct)=freq(B ₂ in controls)  (26)

As a well-accepted sample set is necessary for robust linkagedisequilibrium calculations, data obtained from the International HapMapproject (The International HapMap Consortium 2003, 2005; Thorisson etal, 2005; McVean et al, 2005) can be used for the calculation ofpairwise r² values. Indeed, the samples genotyped for the InternationalHapMap Project were selected to be representative examples from varioushuman sub-populations with sufficient numbers of chromosomes examined todraw meaningful and robust conclusions from the patterns of geneticvariation observed. The International HapMap project website(hapmap.org) contains a description of the project, methods utilized andsamples examined. It is useful to examine empirical data to get a senseof the patterns present in such data.

Haplotype frequencies were explicit arguments in equation (18) above.However, knowing the 2-marker haplotype frequencies requires that phaseto be determined for doubly heterozygous samples. When phase is unknownin the data examined, various algorithms can be used to infer phase fromthe genotype data. This issue was discussed earlier where the doublyheterozygous individual with a 2-SNP genotype of A₁A₂B₂ could have oneof two different sets of chromosomes: A₁B₁/A₂B₂ or A₁B₂/A₂B₁. One suchalgorithm to estimate haplotype frequencies is theexpectation-maximization (EM) algorithm first formalized by Dempster etal. (1977). This algorithm is often used in genetics to infer haplotypefrequencies from genotype data (e.g. Excoffier and Slatkin (1995);Tregouet et al., (2004)). It should be noted that for the two-SNP caseexplored here, EM algorithms have very little error provided that theallele frequencies and sample sizes are not too small. The impact on r²values is typically negligible.

As correlated genetic markers share information, interrogation of SNPmarkers in LD with a disease-associated SNP marker can also havesufficient power to detect disease association (Long and Langley(1999)). The relationship between the power to directly finddisease-associated alleles and the power to indirectly detectdisease-association was investigated by Pritchard and Przeworski (2001).In a straight-forward derivation, it can be shown that the power todetect disease association indirectly at a marker locus in linkagedisequilibrium with a disease-association locus is approximately thesame as the power to detect disease-association directly at thedisease-association locus if the sample size is increased by a factor of

$\frac{1}{r^{2}}$(the reciprocal of equation 18) at the marker in comparison with thedisease-association locus.

Therefore, if one calculated the power to detect disease-associationindirectly with an experiment having N samples, then equivalent power todirectly detect disease-association (at the actualdisease-susceptibility locus) would necessitate an experiment usingapproximately r²N samples. This elementary relationship between power,sample size and linkage disequilibrium can be used to derive an r²threshold value useful in determining whether or not genotyping markersin linkage disequilibrium with a SNP marker directly associated withdisease status has enough power to indirectly detectdisease-association.

To commence a derivation of the power to detect disease-associatedmarkers through an indirect process, define the effective chromosomalsample size as

$\begin{matrix}{{n = \frac{4N_{cs}N_{ct}}{N_{cs} + N_{ct}}};} & (27)\end{matrix}$where N_(cs) and N_(ct) are the numbers of diploid cases and controls,respectively. This is necessary to handle situations where the numbersof cases and controls are not equivalent. For equal case and controlsample sizes, N_(cs)=N_(ct)=N, the value of the effective number ofchromosomes is simply n=2N—as expected. Let power be calculated for asignificance level α (such that traditional P-values below α will bedeemed statistically significant). Define the standard Gaussiandistribution function as Φ(●). Mathematically,

$\begin{matrix}{{\Phi(x)} = {\frac{1}{\sqrt{2\pi}}{\int\limits_{- \infty}^{x}{e^{\frac{\theta^{2}}{2}}d\theta}}}} & (28)\end{matrix}$Alternatively, the following error function notation (Erf) may also beused,

$\begin{matrix}{{\Phi(x)} = {\frac{1}{2}\left\lbrack {1 + {Er{f\ \left( \frac{x}{\sqrt{2}} \right)}}} \right\rbrack}} & (29)\end{matrix}$

For example, Φ(1.644854)=0.95. The value of r² may be derived to yield apre-specified minimum amount of power to detect disease associationthough indirect interrogation. Noting that the LD SNP marker could bethe one that is carrying the disease-association allele, therefore thatthis approach constitutes a lower-bound model where all indirect powerresults are expected to be at least as large as those interrogated.

Denote by β the error rate for not detecting truly disease-associatedmarkers. Therefore, 1-β is the classical definition of statisticalpower. Substituting the Pritchard-Pzreworski result into the samplesize, the power to detect disease association at a significance level ofα is given by the approximation

$\begin{matrix}{{{1 - \beta} \cong {\Phi\left\lbrack {\frac{❘{q_{1,{cs}} - q_{1,{ct}}}❘}{\sqrt{\frac{{q_{1,{cs}}\left( {1 - q_{1,{cs}}} \right)} + {q_{1,{ct}}\left( {1 - q_{1,{ct}}} \right)}}{r^{2}n}}} - Z_{1 - {\alpha/2}}} \right\rbrack}};} & (30)\end{matrix}$where Z_(u) is the inverse of the standard normal cumulativedistribution evaluated at u (u∈(0,1)). Z_(u)=Φ⁻¹ (u), whereΦ(Φ⁻¹(u))=Φ⁻¹(Φ(u))=u. For example, setting α=0.05, and therefore1−α/2=0.975, Z_(0.975)=1.95996 is obtained. Next, setting power equal toa threshold of a minimum power of T,

$\begin{matrix}{T = {\Phi\left\lbrack {\frac{❘{q_{1,{cs}} - q_{1,{ct}}}❘}{\sqrt{\frac{{q_{1,{cs}}\left( {1 - q_{1,{cs}}} \right)} + {q_{1,{ct}}\left( {1 - q_{1,{ct}}} \right)}}{r^{2}n}}} - Z_{1 - {\alpha/2}}} \right\rbrack}} & (31)\end{matrix}$and solving for r², the following threshold r² is obtained:

$\begin{matrix}{{r_{T}^{2} = {\frac{\left\lfloor {{q_{1,{cs}}\left( {1 - q_{1,{cs}}} \right)} + {q_{1,{ct}}\left( {1 - q_{1,{ct}}} \right)}} \right\rfloor}{{n\left( {q_{1,{cs}} - q_{1,{ct}}} \right)}^{2}}\left\lbrack {{\Phi^{- 1}(T)} + Z_{1 - {\alpha/2}}} \right\rbrack}^{2}}{{Or},}} & (32)\end{matrix}$ $\begin{matrix}{r_{T}^{2} = {\frac{\left( {Z_{T} + Z_{1 - {\alpha/2}}} \right)^{2}}{n}\left\lbrack \frac{q_{1,{cs}} - \left( q_{1,{cs}} \right)^{2} + q_{1,{ct}} - \left( q_{1,{ct}} \right)^{2}}{\left( {q_{1,{cs}} - q_{1,{ct}}} \right)^{2}} \right\rbrack}} & (33)\end{matrix}$

Suppose that r² is calculated between an interrogated SNP and a numberof other SNPs with varying levels of LD with the interrogated SNP. Thethreshold value r_(T)2 is the minimum value of linkage disequilibriumbetween the interrogated SNP and the potential LD SNPs such that the LDSNP still retains a power greater or equal to T for detectingdisease-association. For example, suppose that SNP rs200 is genotyped ina case-control disease-association study and it is found to beassociated with a disease phenotype. Further suppose that the minorallele frequency in 1,000 case chromosomes was found to be 16% incontrast with a minor allele frequency of 10% in 1,000 controlchromosomes. Given those measurements one could have predicted, prior tothe experiment, that the power to detect disease association at asignificance level of 0.05 was quite high—approximately 98% using a testof allelic association. Applying equation (32) one can calculate aminimum value of r² to indirectly assess disease association assumingthat the minor allele at SNP rs200 is truly disease-predisposing for athreshold level of power. If one sets the threshold level of power to be80%, then r_(T) ²=0.489 given the same significance level and chromosomenumbers as above. Hence, any SNP with a pairwise r² value with rs200greater than 0.489 is expected to have greater than 80% power to detectthe disease association. Further, this is assuming the conservativemodel where the LD SNP is disease-associated only through linkagedisequilibrium with the interrogated SNP rs200.

The contribution or association of particular SNPs and/or SNP haplotypeswith disease phenotypes, such as psoriasis, enables the SNPs of thepresent invention to be used to develop superior diagnostic testscapable of identifying individuals who express a detectable trait, suchas psoriasis, as the result of a specific genotype, or individuals whosegenotype places them at an increased or decreased risk of developing adetectable trait at a subsequent time as compared to individuals who donot have that genotype. As described herein, diagnostics may be based ona single SNP or a group of SNPs. Combined detection of a plurality ofSNPs (for example, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16,17, 18, 19, 20, 24, 25, 30, 32, 48, 50, 64, 96, 100, or any other numberin-between, or more, of the SNPs provided in Table 1 and/or Table 2)typically increases the probability of an accurate diagnosis. Forexample, the presence of a single SNP known to correlate with psoriasismight indicate a probability of 20% that an individual has or is at riskof developing psoriasis, whereas detection of five SNPs, each of whichcorrelates with psoriasis, might indicate a probability of 80% that anindividual has or is at risk of developing psoriasis. To furtherincrease the accuracy of diagnosis or predisposition screening, analysisof the SNPs of the present invention can be combined with that of otherpolymorphisms or other risk factors of psoriasis, such as diseasesymptoms, pathological characteristics, family history, diet,environmental factors or lifestyle factors.

It will, of course, be understood by practitioners skilled in thetreatment or diagnosis of psoriasis that the present invention generallydoes not intend to provide an absolute identification of individuals whoare at risk (or less at risk) of developing psoriasis, and/orpathologies related to psoriasis, but rather to indicate a certainincreased (or decreased) degree or likelihood of developing the diseasebased on statistically significant association results. However, thisinformation is extremely valuable as it can be used to, for example,initiate preventive treatments or to allow an individual carrying one ormore significant SNPs or SNP haplotypes to foresee warning signs such asminor clinical symptoms, or to have regularly scheduled physical examsto monitor for appearance of a condition in order to identify and begintreatment of the condition at an early stage. Particularly with diseasesthat are extremely debilitating or fatal if not treated on time, theknowledge of a potential predisposition, even if this predisposition isnot absolute, would likely contribute in a very significant manner totreatment efficacy.

The diagnostic techniques of the present invention may employ a varietyof methodologies to determine whether a test subject has a SNP or a SNPpattern associated with an increased or decreased risk of developing adetectable trait or whether the individual suffers from a detectabletrait as a result of a particular polymorphism/mutation, including, forexample, methods which enable the analysis of individual chromosomes forhaplotyping, family studies, single sperm DNA analysis, or somatichybrids. The trait analyzed using the diagnostics of the invention maybe any detectable trait that is commonly observed in pathologies anddisorders related to psoriasis.

Another aspect of the present invention relates to a method ofdetermining whether an individual is at risk (or less at risk) ofdeveloping one or more traits or whether an individual expresses one ormore traits as a consequence of possessing a particular trait-causing ortrait-influencing allele. These methods generally involve obtaining anucleic acid sample from an individual and assaying the nucleic acidsample to determine which nucleotide(s) is/are present at one or moreSNP positions, wherein the assayed nucleotide(s) is/are indicative of anincreased or decreased risk of developing the trait or indicative thatthe individual expresses the trait as a result of possessing aparticular trait-causing or trait-influencing allele.

In another embodiment, the SNP detection reagents of the presentinvention are used to determine whether an individual has one or moreSNP allele(s) affecting the level (e.g., the concentration of mRNA orprotein in a sample, etc.) or pattern (e.g., the kinetics of expression,rate of decomposition, stability profile, Km, Vmax, etc.) of geneexpression (collectively, the “gene response” of a cell or bodilyfluid). Such a determination can be accomplished by screening for mRNAor protein expression (e.g., by using nucleic acid arrays, RT-PCR,TaqMan assays, or mass spectrometry), identifying genes having alteredexpression in an individual, genotyping SNPs disclosed in Table 1 and/orTable 2 that could affect the expression of the genes having alteredexpression (e.g., SNPs that are in and/or around the gene(s) havingaltered expression, SNPs in regulatory/control regions, SNPs in and/oraround other genes that are involved in pathways that could affect theexpression of the gene(s) having altered expression, or all SNPs couldbe genotyped), and correlating SNP genotypes with altered geneexpression. In this manner, specific SNP alleles at particular SNP sitescan be identified that affect gene expression.

Pharmacogenomics and Therapeutics/Drug Development

The present invention provides methods for assessing thepharmacogenomics of a subject harboring particular SNP alleles orhaplotypes or diplotypes to a particular therapeutic agent orpharmaceutical compound, or to a class of such compounds.Pharmacogenomics deals with the roles which clinically significanthereditary variations (e.g., SNPs) play in the response to drugs due toaltered drug disposition and/or abnormal action in affected persons.See, e.g., Roses, Nature 405, 857-865 (2000); Gould Rothberg, NatureBiotechnology 19, 209-211 (2001); Eichelbaum, Clin. Exp. Pharmacol.Physiol. 23(10-11):983-985 (1996); and Linder, Clin. Chem. 43(2):254-266(1997). The clinical outcomes of these variations can result in severetoxicity of therapeutic drugs in certain individuals or therapeuticfailure of drugs in certain individuals as a result of individualvariation in metabolism. Thus, the SNP genotype of an individual candetermine the way a therapeutic compound acts on the body or the way thebody metabolizes the compound. For example, SNPs in drug metabolizingenzymes can affect the activity of these enzymes, which in turn canaffect both the intensity and duration of drug action, as well as drugmetabolism and clearance.

The discovery of SNPs in drug metabolizing enzymes, drug transporters,proteins for pharmaceutical agents, and other drug targets has explainedwhy some patients do not obtain the expected drug effects, show anexaggerated drug effect, or experience serious toxicity from standarddrug dosages. SNPs can be expressed in the phenotype of the extensivemetabolizer and in the phenotype of the poor metabolizer. Accordingly,SNPs may lead to allelic variants of a protein in which one or more ofthe protein functions in one population are different from those inanother population. SNPs and the encoded variant peptides thus providetargets to ascertain a genetic predisposition that can affect treatmentmodality. For example, in a ligand-based treatment, SNPs may give riseto amino terminal extracellular domains and/or other ligand-bindingregions of a receptor that are more or less active in ligand binding,thereby affecting subsequent protein activation. Accordingly, liganddosage would necessarily be modified to maximize the therapeutic effectwithin a given population containing particular SNP alleles orhaplotypes.

As an alternative to genotyping, specific variant proteins containingvariant amino acid sequences encoded by alternative SNP alleles could beidentified. Thus, pharmacogenomic characterization of an individualpermits the selection of effective compounds and effective dosages ofsuch compounds for prophylactic or therapeutic uses based on theindividual's SNP genotype, thereby enhancing and optimizing theeffectiveness of the therapy. Furthermore, the production of recombinantcells and transgenic animals containing particular SNPs/haplotypes alloweffective clinical design and testing of treatment compounds and dosageregimens. For example, transgenic animals can be produced that differonly in specific SNP alleles in a gene that is orthologous to a humandisease susceptibility gene.

Pharmacogenomic uses of the SNPs of the present invention provideseveral significant advantages for patient care, particularly intreating psoriasis. Pharmacogenomic characterization of an individual,based on an individual's SNP genotype, can identify those individualsunlikely to respond to treatment with a particular medication andthereby allows physicians to avoid prescribing the ineffectivemedication to those individuals. On the other hand, SNP genotyping of anindividual may enable physicians to select the appropriate medicationand dosage regimen that will be most effective based on an individual'sSNP genotype. This information increases a physician's confidence inprescribing medications and motivates patients to comply with their drugregimens. Furthermore, pharmacogenomics may identify patientspredisposed to toxicity and adverse reactions to particular drugs ordrug dosages. Adverse drug reactions lead to more than 100,000 avoidabledeaths per year in the United States alone and therefore represent asignificant cause of hospitalization and death, as well as a significanteconomic burden on the healthcare system (Pfost et. al., Trends inBiotechnology, August 2000.). Thus, pharmacogenomics based on the SNPsdisclosed herein has the potential to both save lives and reducehealthcare costs substantially.

Attempts have been made to develop drugs that can be used to treatpsoriasis. Several drug candidates have been introduced into clinicaltrials to test their efficacy in treating psoriasis. Among them areABT-874, STA-5326, and CNTO-1275. For references discussing these drugs,please see Burakoff, et al., A phase 1/2A trial of STA 5326, an oralinterleukin-12/23 inhibitor, in patients with active moderate to severeCrohn's disease. Inflamm Bowel Dis. 2006 July; 12(7):558-65, andBorchardt J K, Focus on small molecule inhibitors for treatment ofinflammatory and autoimmune diseases. Drug News Perspect. 2004 November;17(9):607-14 (for STA-5326); Sandborn W J, How future tumor necrosisfactor antagonists and other compounds will meet the remainingchallenges in Crohn's disease. Rev Gastroenterol Disord. 2004; 4 Suppl3:S25-33 (for ABT-874); Papp K A. Potential future therapies forpsoriasis. Semin Cutan Med Surg. 2005 March; 24(1):58-63 (forCNTO-1275). These drug candidates target the metabolic pathway involvingIL-12 and IL-23 genes.

It is also well known in the art that markers that are diagnosticallyuseful in distinguishing patients at higher risk of developing adisease, such as psoriasis from those who are at a decreased risk ofdeveloping psoriasis can be useful in identifying those patients thatare more likely to respond to drug treatments targeting at thosepathways involving genes where the diagnostic SNPs reside. Seereferences Gerdes, et al., Circulation, 2000; 101:1366-1371,Kuivenhoven, et al., N Engl J Med 1998; 338:86-93, Stolarz, et al.,Hypertension 2004; 44:156-162, Chartier-Harlin, et al., Hum. Mol. Genet.1994 April; 3(4):569-74, Roses, et al., The Pharmacogenomics Journal2006, 1-19.

In that regard, embodiments of the present invention can be very usefulin assisting clinicians select patients who are more likely to developpsoriasis, and are in turn good candidates for drug responses targetingpsoriasis, thus warrant the application of the above-mentioned drugtreatments on such patients. In the mean time, patients who are deemedto have low risk of developing psoriasis, using SNP markers discoveredherein, can be spared of the aggravation and wastfulness of the drug dueto the reduced benefit of such treatment in view of its cost and sideeffect.

Pharmacogenomics in general is discussed further in Rose et al.,“Pharmacogenetic analysis of clinically relevant genetic polymorphisms”,Methods Mol Med. 2003; 85:225-37. Pharmacogenomics as it relates toAlzheimer's disease and other neurodegenerative disorders is discussedin Cacabelos, “Pharmacogenomics for the treatment of dementia”, Ann Med.2002; 34(5):357-79, Maimone et al., “Pharmacogenomics ofneurodegenerative diseases”, Eur J Pharmacol. 2001 Feb. 9; 413(1):11-29,and Poirier, “Apolipoprotein E: a pharmacogenetic target for thetreatment of Alzheimer's disease”, Mol Diagn. 1999 December;4(4):335-41. Pharmacogenomics as it relates to cardiovascular disordersis discussed in Siest et al., “Pharmacogenomics of drugs affecting thecardiovascular system”, Clin Chem Lab Med. 2003 April; 41(4):590-9,Mukherjee et al., “Pharmacogenomics in cardiovascular diseases”, ProgCardiovasc Dis. 2002 May-June; 44(6):479-98, and Mooser et al.,“Cardiovascular pharmacogenetics in the SNP era”, J Thromb Haemost. 2003July; 1(7):1398-402. Pharmacogenomics as it relates to cancer isdiscussed in McLeod et al., “Cancer pharmacogenomics: SNPs, chips, andthe individual patient”, Cancer Invest. 2003; 21(4):630-40 and Watterset al., “Cancer pharmacogenomics: current and future applications”,Biochim Biophys Acta. 2003 Mar. 17; 1603(2):99-111.

The SNPs of the present invention also can be used to identify noveltherapeutic targets for psoriasis. For example, genes containing thedisease-associated variants (“variant genes”) or their products, as wellas genes or their products that are directly or indirectly regulated byor interacting with these variant genes or their products, can betargeted for the development of therapeutics that, for example, treatthe disease or prevent or delay disease onset. The therapeutics may becomposed of, for example, small molecules, proteins, protein fragmentsor peptides, antibodies, nucleic acids, or their derivatives or mimeticswhich modulate the functions or levels of the target genes or geneproducts.

The SNP-containing nucleic acid molecules disclosed herein, and theircomplementary nucleic acid molecules, may be used as antisenseconstructs to control gene expression in cells, tissues, and organisms.Antisense technology is well established in the art and extensivelyreviewed in Antisense Drug Technology: Principles, Strategies, andApplications, Crooke (ed.), Marcel Dekker, Inc.: New York (2001). Anantisense nucleic acid molecule is generally designed to becomplementary to a region of mRNA expressed by a gene so that theantisense molecule hybridizes to the mRNA and thereby blocks translationof mRNA into protein. Various classes of antisense oligonucleotides areused in the art, two of which are cleavers and blockers. Cleavers, bybinding to target RNAs, activate intracellular nucleases (e.g., RNase Hor RNase L) that cleave the target RNA. Blockers, which also bind totarget RNAs, inhibit protein translation through steric hindrance ofribosomes. Exemplary blockers include peptide nucleic acids,morpholinos, locked nucleic acids, and methylphosphonates (see, e.g.,Thompson, Drug Discovery Today, 7 (17): 912-917 (2002)). Antisenseoligonucleotides are directly useful as therapeutic agents, and are alsouseful for determining and validating gene function (e.g., in geneknock-out or knock-down experiments).

Antisense technology is further reviewed in: Lavery et al., “Antisenseand RNAi: powerful tools in drug target discovery and validation”, CurrOpin Drug Discov Devel. 2003 July; 6(4):561-9; Stephens et al.,“Antisense oligonucleotide therapy in cancer”, Curr Opin Mol Ther. 2003April; 5(2):118-22; Kurreck, “Antisense technologies. Improvementthrough novel chemical modifications”, Eur J Biochem. 2003 April;270(8):1628-44; Dias et al., “Antisense oligonucleotides: basic conceptsand mechanisms”, Mol Cancer Ther. 2002 March; 1(5):347-55; Chen,“Clinical development of antisense oligonucleotides as anti-cancertherapeutics”, Methods Mol Med. 2003; 75:621-46; Wang et al., “Antisenseanticancer oligonucleotide therapeutics”, Curr Cancer Drug Targets. 2001November; 1(3):177-96; and Bennett, “Efficiency of antisenseoligonucleotide drug discovery”, Antisense Nucleic Acid Drug Dev. 2002June; 12(3):215-24.

The SNPs of the present invention are particularly useful for designingantisense reagents that are specific for particular nucleic acidvariants. Based on the SNP information disclosed herein, antisenseoligonucleotides can be produced that specifically target mRNA moleculesthat contain one or more particular SNP nucleotides. In this manner,expression of mRNA molecules that contain one or more undesiredpolymorphisms (e.g., SNP nucleotides that lead to a defective proteinsuch as an amino acid substitution in a catalytic domain) can beinhibited or completely blocked. Thus, antisense oligonucleotides can beused to specifically bind a particular polymorphic form (e.g., a SNPallele that encodes a defective protein), thereby inhibiting translationof this form, but which do not bind an alternative polymorphic form(e.g., an alternative SNP nucleotide that encodes a protein havingnormal function).

Antisense molecules can be used to inactivate mRNA in order to inhibitgene expression and production of defective proteins. Accordingly, thesemolecules can be used to treat a disorder, such as psoriasis,characterized by abnormal or undesired gene expression or expression ofcertain defective proteins. This technique can involve cleavage by meansof ribozymes containing nucleotide sequences complementary to one ormore regions in the mRNA that attenuate the ability of the mRNA to betranslated. Possible mRNA regions include, for example, protein-codingregions and particularly protein-coding regions corresponding tocatalytic activities, substrate/ligand binding, or other functionalactivities of a protein.

The SNPs of the present invention are also useful for designing RNAinterference reagents that specifically target nucleic acid moleculeshaving particular SNP variants. RNA interference (RNAi), also referredto as gene silencing, is based on using double-stranded RNA (dsRNA)molecules to turn genes off. When introduced into a cell, dsRNAs areprocessed by the cell into short fragments (generally about 21, 22, or23 nucleotides in length) known as small interfering RNAs (siRNAs) whichthe cell uses in a sequence-specific manner to recognize and destroycomplementary RNAs (Thompson, Drug Discovery Today, 7 (17): 912-917(2002)). Accordingly, an aspect of the present invention specificallycontemplates isolated nucleic acid molecules that are about 18-26nucleotides in length, preferably 19-25 nucleotides in length, and morepreferably 20, 21, 22, or 23 nucleotides in length, and the use of thesenucleic acid molecules for RNAi. Because RNAi molecules, includingsiRNAs, act in a sequence-specific manner, the SNPs of the presentinvention can be used to design RNAi reagents that recognize and destroynucleic acid molecules having specific SNP alleles/nucleotides (such asdeleterious alleles that lead to the production of defective proteins),while not affecting nucleic acid molecules having alternative SNPalleles (such as alleles that encode proteins having normal function).As with antisense reagents, RNAi reagents may be directly useful astherapeutic agents (e.g., for turning off defective, disease-causinggenes), and are also useful for characterizing and validating genefunction (e.g., in gene knock-out or knock-down experiments).

The following references provide a further review of RNAi: Reynolds etal., “Rational siRNA design for RNA interference”, Nat Biotechnol. 2004March; 22(3):326-30. Epub 2004 Feb. 1; Chi et al., “Genomewide view ofgene silencing by small interfering RNAs”, PNAS 100(11):6343-6346, 2003;Vickers et al., “Efficient Reduction of Target RNAs by Small InterferingRNA and RNase H-dependent Antisense Agents”, J. Biol. Chem. 278:7108-7118, 2003; Agami, “RNAi and related mechanisms and their potentialuse for therapy”, Curr Opin Chem Biol. 2002 December; 6(6):829-34;Lavery et al., “Antisense and RNAi: powerful tools in drug targetdiscovery and validation”, Curr Opin Drug Discov Devel. 2003 July;6(4):561-9; Shi, “Mammalian RNAi for the masses”, Trends Genet 2003January; 19(1):9-12), Shuey et al., “RNAi: gene-silencing in therapeuticintervention”, Drug Discovery Today 2002 October; 7(20):1040-1046;McManus et al., Nat Rev Genet 2002 October; 3(10):737-47; Xia et al.,Nat Biotechnol 2002 October; 20(10):1006-10; Plasterk et al., Curr OpinGenet Dev 2000 October; 10(5):562-7; Bosher et al., Nat Cell Biol 2000February; 2(2):E31-6; and Hunter, Curr Biol 1999 Jun. 17; 9(12):R440-2).

A subject suffering from a pathological condition, such as psoriasis,ascribed to a SNP may be treated so as to correct the genetic defect(see Kren et al., Proc. Natl. Acad. Sci. USA 96:10349-10354 (1999)).Such a subject can be identified by any method that can detect thepolymorphism in a biological sample drawn from the subject. Such agenetic defect may be permanently corrected by administering to such asubject a nucleic acid fragment incorporating a repair sequence thatsupplies the normal/wild-type nucleotide at the position of the SNP.This site-specific repair sequence can encompass an RNA/DNAoligonucleotide that operates to promote endogenous repair of asubject's genomic DNA. The site-specific repair sequence is administeredin an appropriate vehicle, such as a complex with polyethylenimine,encapsulated in anionic liposomes, a viral vector such as an adenovirus,or other pharmaceutical composition that promotes intracellular uptakeof the administered nucleic acid. A genetic defect leading to an inbornpathology may then be overcome, as the chimeric oligonucleotides induceincorporation of the normal sequence into the subject's genome. Uponincorporation, the normal gene product is expressed, and the replacementis propagated, thereby engendering a permanent repair and therapeuticenhancement of the clinical condition of the subject.

In cases in which a cSNP results in a variant protein that is ascribedto be the cause of, or a contributing factor to, a pathologicalcondition, a method of treating such a condition can includeadministering to a subject experiencing the pathology thewild-type/normal cognate of the variant protein. Once administered in aneffective dosing regimen, the wild-type cognate provides complementationor remediation of the pathological condition.

The invention further provides a method for identifying a compound oragent that can be used to treat psoriasis. The SNPs disclosed herein areuseful as targets for the identification and/or development oftherapeutic agents. A method for identifying a therapeutic agent orcompound typically includes assaying the ability of the agent orcompound to modulate the activity and/or expression of a SNP-containingnucleic acid or the encoded product and thus identifying an agent or acompound that can be used to treat a disorder characterized by undesiredactivity or expression of the SNP-containing nucleic acid or the encodedproduct. The assays can be performed in cell-based and cell-freesystems. Cell-based assays can include cells naturally expressing thenucleic acid molecules of interest or recombinant cells geneticallyengineered to express certain nucleic acid molecules.

Variant gene expression in a psoriasis patient can include, for example,either expression of a SNP-containing nucleic acid sequence (forinstance, a gene that contains a SNP can be transcribed into an mRNAtranscript molecule containing the SNP, which can in turn be translatedinto a variant protein) or altered expression of a normal/wild-typenucleic acid sequence due to one or more SNPs (for instance, aregulatory/control region can contain a SNP that affects the level orpattern of expression of a normal transcript).

Assays for variant gene expression can involve direct assays of nucleicacid levels (e.g., mRNA levels), expressed protein levels, or ofcollateral compounds involved in a signal pathway. Further, theexpression of genes that are up- or down-regulated in response to thesignal pathway can also be assayed. In this embodiment, the regulatoryregions of these genes can be operably linked to a reporter gene such asluciferase.

Modulators of variant gene expression can be identified in a methodwherein, for example, a cell is contacted with a candidatecompound/agent and the expression of mRNA determined. The level ofexpression of mRNA in the presence of the candidate compound is comparedto the level of expression of mRNA in the absence of the candidatecompound. The candidate compound can then be identified as a modulatorof variant gene expression based on this comparison and be used to treata disorder such as psoriasis that is characterized by variant geneexpression (e.g., either expression of a SNP-containing nucleic acid oraltered expression of a normal/wild-type nucleic acid molecule due toone or more SNPs that affect expression of the nucleic acid molecule)due to one or more SNPs of the present invention. When expression ofmRNA is statistically significantly greater in the presence of thecandidate compound than in its absence, the candidate compound isidentified as a stimulator of nucleic acid expression. When nucleic acidexpression is statistically significantly less in the presence of thecandidate compound than in its absence, the candidate compound isidentified as an inhibitor of nucleic acid expression.

The invention further provides methods of treatment, with the SNP orassociated nucleic acid domain (e.g., catalytic domain,ligand/substrate-binding domain, regulatory/control region, etc.) orgene, or the encoded mRNA transcript, as a target, using a compoundidentified through drug screening as a gene modulator to modulatevariant nucleic acid expression. Modulation can include eitherup-regulation (i.e., activation or agonization) or down-regulation(i.e., suppression or antagonization) of nucleic acid expression.

Expression of mRNA transcripts and encoded proteins, either wild type orvariant, may be altered in individuals with a particular SNP allele in aregulatory/control element, such as a promoter or transcription factorbinding domain, that regulates expression. In this situation, methods oftreatment and compounds can be identified, as discussed herein, thatregulate or overcome the variant regulatory/control element, therebygenerating normal, or healthy, expression levels of either the wild typeor variant protein.

The SNP-containing nucleic acid molecules of the present invention arealso useful for monitoring the effectiveness of modulating compounds onthe expression or activity of a variant gene, or encoded product, inclinical trials or in a treatment regimen. Thus, the gene expressionpattern can serve as an indicator for the continuing effectiveness oftreatment with the compound, particularly with compounds to which apatient can develop resistance, as well as an indicator for toxicities.The gene expression pattern can also serve as a marker indicative of aphysiological response of the affected cells to the compound.Accordingly, such monitoring would allow either increased administrationof the compound or the administration of alternative compounds to whichthe patient has not become resistant. Similarly, if the level of nucleicacid expression falls below a desirable level, administration of thecompound could be commensurately decreased.

In another aspect of the present invention, there is provided apharmaceutical pack comprising a therapeutic agent (e.g., a smallmolecule drug, antibody, peptide, antisense or RNAi nucleic acidmolecule, etc.) and a set of instructions for administration of thetherapeutic agent to humans diagnostically tested for one or more SNPsor SNP haplotypes provided by the present invention.

The SNPs/haplotypes of the present invention are also useful forimproving many different aspects of the drug development process. Forinstance, an aspect of the present invention includes selectingindividuals for clinical trials based on their SNP genotype. Forexample, individuals with SNP genotypes that indicate that they arelikely to positively respond to a drug can be included in the trials,whereas those individuals whose SNP genotypes indicate that they areless likely to or would not respond to the drug, or who are at risk forsuffering toxic effects or other adverse reactions, can be excluded fromthe clinical trials. This not only can improve the safety of clinicaltrials, but also can enhance the chances that the trial will demonstratestatistically significant efficacy. Furthermore, the SNPs of the presentinvention may explain why certain previously developed drugs performedpoorly in clinical trials and may help identify a subset of thepopulation that would benefit from a drug that had previously performedpoorly in clinical trials, thereby “rescuing” previously developeddrugs, and enabling the drug to be made available to a particularpsoriasis patient population that can benefit from it.

SNPs have many important uses in drug discovery, screening, anddevelopment. A high probability exists that, for any gene/proteinselected as a potential drug target, variants of that gene/protein willexist in a patient population. Thus, determining the impact ofgene/protein variants on the selection and delivery of a therapeuticagent should be an integral aspect of the drug discovery and developmentprocess. (Jazwinska, A Trends Guide to Genetic Variation and GenomicMedicine, 2002 March; S30-S36).

Knowledge of variants (e.g., SNPs and any corresponding amino acidpolymorphisms) of a particular therapeutic target (e.g., a gene, mRNAtranscript, or protein) enables parallel screening of the variants inorder to identify therapeutic candidates (e.g., small moleculecompounds, antibodies, antisense or RNAi nucleic acid compounds, etc.)that demonstrate efficacy across variants (Rothberg, Nat Biotechnol 2001March; 19(3):209-11). Such therapeutic candidates would be expected toshow equal efficacy across a larger segment of the patient population,thereby leading to a larger potential market for the therapeuticcandidate.

Furthermore, identifying variants of a potential therapeutic targetenables the most common form of the target to be used for selection oftherapeutic candidates, thereby helping to ensure that the experimentalactivity that is observed for the selected candidates reflects the realactivity expected in the largest proportion of a patient population(Jazwinska, A Trends Guide to Genetic Variation and Genomic Medicine,2002 March; S30-S36).

Additionally, screening therapeutic candidates against all knownvariants of a target can enable the early identification of potentialtoxicities and adverse reactions relating to particular variants. Forexample, variability in drug absorption, distribution, metabolism andexcretion (ADME) caused by, for example, SNPs in therapeutic targets ordrug metabolizing genes, can be identified, and this information can beutilized during the drug development process to minimize variability indrug disposition and develop therapeutic agents that are safer across awider range of a patient population. The SNPs of the present invention,including the variant proteins and encoding polymorphic nucleic acidmolecules provided in Tables 1-2, are useful in conjunction with avariety of toxicology methods established in the art, such as those setforth in Current Protocols in Toxicology, John Wiley & Sons, Inc., N.Y.

Furthermore, therapeutic agents that target any art-known proteins (ornucleic acid molecules, either RNA or DNA) may cross-react with thevariant proteins (or polymorphic nucleic acid molecules) disclosed inTable 1, thereby significantly affecting the pharmacokinetic propertiesof the drug. Consequently, the protein variants and the SNP-containingnucleic acid molecules disclosed in Tables 1-2 are useful in developing,screening, and evaluating therapeutic agents that target correspondingart-known protein forms (or nucleic acid molecules). Additionally, asdiscussed above, knowledge of all polymorphic forms of a particular drugtarget enables the design of therapeutic agents that are effectiveagainst most or all such polymorphic forms of the drug target.

Pharmaceutical Compositions and Administration Thereof

Any of the psoriasis-associated proteins, and encoding nucleic acidmolecules, disclosed herein can be used as therapeutic targets (ordirectly used themselves as therapeutic compounds) for treatingpsoriasis and related pathologies, and the present disclosure enablestherapeutic compounds (e.g., small molecules, antibodies, therapeuticproteins, RNAi and antisense molecules, etc.) to be developed thattarget (or are comprised of) any of these therapeutic targets.

In general, a therapeutic compound will be administered in atherapeutically effective amount by any of the accepted modes ofadministration for agents that serve similar utilities. The actualamount of the therapeutic compound of this invention, i.e., the activeingredient, will depend upon numerous factors such as the severity ofthe disease to be treated, the age and relative health of the subject,the potency of the compound used, the route and form of administration,and other factors.

Therapeutically effective amounts of therapeutic compounds may rangefrom, for example, approximately 0.01-50 mg per kilogram body weight ofthe recipient per day; preferably about 0.1-20 mg/kg/day. Thus, as anexample, for administration to a 70 kg person, the dosage range wouldmost preferably be about 7 mg to 1.4 g per day.

In general, therapeutic compounds will be administered as pharmaceuticalcompositions by any one of the following routes: oral, systemic (e.g.,transdermal, intranasal, or by suppository), or parenteral (e.g.,intramuscular, intravenous, or subcutaneous) administration. Thepreferred manner of administration is oral or parenteral using aconvenient daily dosage regimen, which can be adjusted according to thedegree of affliction. Oral compositions can take the form of tablets,pills, capsules, semisolids, powders, sustained release formulations,solutions, suspensions, elixirs, aerosols, or any other appropriatecompositions.

The choice of formulation depends on various factors such as the mode ofdrug administration (e.g., for oral administration, formulations in theform of tablets, pills, or capsules are preferred) and thebioavailability of the drug substance. Recently, pharmaceuticalformulations have been developed especially for drugs that show poorbioavailability based upon the principle that bioavailability can beincreased by increasing the surface area, i.e., decreasing particlesize. For example, U.S. Pat. No. 4,107,288 describes a pharmaceuticalformulation having particles in the size range from 10 to 1,000 nm inwhich the active material is supported on a cross-linked matrix ofmacromolecules. U.S. Pat. No. 5,145,684 describes the production of apharmaceutical formulation in which the drug substance is pulverized tonanoparticles (average particle size of 400 nm) in the presence of asurface modifier and then dispersed in a liquid medium to give apharmaceutical formulation that exhibits remarkably highbioavailability.

Pharmaceutical compositions are comprised of, in general, a therapeuticcompound in combination with at least one pharmaceutically acceptableexcipient. Acceptable excipients are non-toxic, aid administration, anddo not adversely affect the therapeutic benefit of the therapeuticcompound. Such excipients may be any solid, liquid, semi-solid or, inthe case of an aerosol composition, gaseous excipient that is generallyavailable to one skilled in the art.

Solid pharmaceutical excipients include starch, cellulose, talc,glucose, lactose, sucrose, gelatin, malt, rice, flour, chalk, silicagel, magnesium stearate, sodium stearate, glycerol monostearate, sodiumchloride, dried skim milk and the like. Liquid and semisolid excipientsmay be selected from glycerol, propylene glycol, water, ethanol andvarious oils, including those of petroleum, animal, vegetable orsynthetic origin, e.g., peanut oil, soybean oil, mineral oil, sesameoil, etc. Preferred liquid carriers, particularly for injectablesolutions, include water, saline, aqueous dextrose, and glycols.

Compressed gases may be used to disperse a compound of this invention inaerosol form. Inert gases suitable for this purpose are nitrogen, carbondioxide, etc.

Other suitable pharmaceutical excipients and their formulations aredescribed in Remington's Pharmaceutical Sciences, edited by E. W. Martin(Mack Publishing Company, 18^(th) ed., 1990).

The amount of the therapeutic compound in a formulation can vary withinthe full range employed by those skilled in the art. Typically, theformulation will contain, on a weight percent (wt %) basis, from about0.01-99.99 wt % of the therapeutic compound based on the totalformulation, with the balance being one or more suitable pharmaceuticalexcipients. Preferably, the compound is present at a level of about 1-80wt %.

Therapeutic compounds can be administered alone or in combination withother therapeutic compounds or in combination with one or more otheractive ingredient(s). For example, an inhibitor or stimulator of apsoriasis-associated protein can be administered in combination withanother agent that inhibits or stimulates the activity of the same or adifferent psoriasis-associated protein to thereby counteract the affectsof psoriasis.

For further information regarding pharmacology, see Current Protocols inPharmacology, John Wiley & Sons, Inc., N.Y.

Human Identification Applications

In addition to their diagnostic and therapeutic uses in psoriasis andrelated pathologies, the SNPs provided by the present invention are alsouseful as human identification markers for such applications asforensics, paternity testing, and biometrics (see, e.g., Gill, “Anassessment of the utility of single nucleotide polymorphisms (SNPs) forforensic purposes”, Int J Legal Med. 2001; 114(4-5):204-10). Geneticvariations in the nucleic acid sequences between individuals can be usedas genetic markers to identify individuals and to associate a biologicalsample with an individual. Determination of which nucleotides occupy aset of SNP positions in an individual identifies a set of SNP markersthat distinguishes the individual. The more SNP positions that areanalyzed, the lower the probability that the set of SNPs in oneindividual is the same as that in an unrelated individual. Preferably,if multiple sites are analyzed, the sites are unlinked (i.e., inheritedindependently). Thus, preferred sets of SNPs can be selected from amongthe SNPs disclosed herein, which may include SNPs on differentchromosomes, SNPs on different chromosome arms, and/or SNPs that aredispersed over substantial distances along the same chromosome arm.

Furthermore, among the SNPs disclosed herein, preferred SNPs for use incertain forensic/human identification applications include SNPs locatedat degenerate codon positions (i.e., the third position in certaincodons which can be one of two or more alternative nucleotides and stillencode the same amino acid), since these SNPs do not affect the encodedprotein. SNPs that do not affect the encoded protein are expected to beunder less selective pressure and are therefore expected to be morepolymorphic in a population, which is typically an advantage forforensic/human identification applications. However, for certainforensics/human identification applications, such as predictingphenotypic characteristics (e.g., inferring ancestry or inferring one ormore physical characteristics of an individual) from a DNA sample, itmay be desirable to utilize SNPs that affect the encoded protein.

For many of the SNPs disclosed in Tables 1-2 (which are identified as“Applera” SNP source), Tables 1-2 provide SNP allele frequenciesobtained by re-sequencing the DNA of chromosomes from 39 individuals(Tables 1-2 also provide allele frequency information for “Celera”source SNPs and, where available, public SNPs from dbEST, HGBASE, and/orHGMD). The allele frequencies provided in Tables 1-2 enable these SNPsto be readily used for human identification applications. Although anySNP disclosed in Table 1 and/or Table 2 could be used for humanidentification, the closer that the frequency of the minor allele at aparticular SNP site is to 50%, the greater the ability of that SNP todiscriminate between different individuals in a population since itbecomes increasingly likely that two randomly selected individuals wouldhave different alleles at that SNP site. Using the SNP allelefrequencies provided in Tables 1-2, one of ordinary skill in the artcould readily select a subset of SNPs for which the frequency of theminor allele is, for example, at least 1%, 2%, 5%, 10%, 20%, 25%, 30%,40%, 45%, or 50%, or any other frequency in-between. Thus, since Tables1-2 provide allele frequencies based on the re-sequencing of thechromosomes from 39 individuals, a subset of SNPs could readily beselected for human identification in which the total allele count of theminor allele at a particular SNP site is, for example, at least 1, 2, 4,8, 10, 16, 20, 24, 30, 32, 36, 38, 39, 40, or any other numberin-between.

Furthermore, Tables 1-2 also provide population group (interchangeablyreferred to herein as ethnic or racial groups) information coupled withthe extensive allele frequency information. For example, the group of 39individuals whose DNA was re-sequenced was made-up of 20 Caucasians and19 African-Americans. This population group information enables furtherrefinement of SNP selection for human identification. For example,preferred SNPs for human identification can be selected from Tables 1-2that have similar allele frequencies in both the Caucasian andAfrican-American populations; thus, for example, SNPs can be selectedthat have equally high discriminatory power in both populations.Alternatively, SNPs can be selected for which there is a statisticallysignificant difference in allele frequencies between the Caucasian andAfrican-American populations (as an extreme example, a particular allelemay be observed only in either the Caucasian or the African-Americanpopulation group but not observed in the other population group); suchSNPs are useful, for example, for predicting the race/ethnicity of anunknown perpetrator from a biological sample such as a hair or bloodstain recovered at a crime scene. For a discussion of using SNPs topredict ancestry from a DNA sample, including statistical methods, seeFrudakis et al., “A Classifier for the SNP-Based Inference of Ancestry”,Journal of Forensic Sciences 2003; 48(4):771-782.

SNPs have numerous advantages over other types of polymorphic markers,such as short tandem repeats (STRs). For example, SNPs can be easilyscored and are amenable to automation, making SNPs the markers of choicefor large-scale forensic databases. SNPs are found in much greaterabundance throughout the genome than repeat polymorphisms. Populationfrequencies of two polymorphic forms can usually be determined withgreater accuracy than those of multiple polymorphic forms atmulti-allelic loci. SNPs are mutationaly more stable than repeatpolymorphisms. SNPs are not susceptible to artefacts such as stutterbands that can hinder analysis. Stutter bands are frequently encounteredwhen analyzing repeat polymorphisms, and are particularly troublesomewhen analyzing samples such as crime scene samples that may containmixtures of DNA from multiple sources. Another significant advantage ofSNP markers over STR markers is the much shorter length of nucleic acidneeded to score a SNP. For example, STR markers are generally severalhundred base pairs in length. A SNP, on the other hand, comprises asingle nucleotide, and generally a short conserved region on either sideof the SNP position for primer and/or probe binding. This makes SNPsmore amenable to typing in highly degraded or aged biological samplesthat are frequently encountered in forensic casework in which DNA may befragmented into short pieces.

SNPs also are not subject to microvariant and “off-ladder” allelesfrequently encountered when analyzing STR loci. Microvariants aredeletions or insertions within a repeat unit that change the size of theamplified DNA product so that the amplified product does not migrate atthe same rate as reference alleles with normal sized repeat units. Whenseparated by size, such as by electrophoresis on a polyacrylamide gel,microvariants do not align with a reference allelic ladder of standardsized repeat units, but rather migrate between the reference alleles.The reference allelic ladder is used for precise sizing of alleles forallele classification; therefore alleles that do not align with thereference allelic ladder lead to substantial analysis problems.Furthermore, when analyzing multi-allelic repeat polymorphisms,occasionally an allele is found that consists of more or less repeatunits than has been previously seen in the population, or more or lessrepeat alleles than are included in a reference allelic ladder. Thesealleles will migrate outside the size range of known alleles in areference allelic ladder, and therefore are referred to as “off-ladder”alleles. In extreme cases, the allele may contain so few or so manyrepeats that it migrates well out of the range of the reference allelicladder. In this situation, the allele may not even be observed, or, withmultiplex analysis, it may migrate within or close to the size range foranother locus, further confounding analysis.

SNP analysis avoids the problems of microvariants and off-ladder allelesencountered in STR analysis. Importantly, microvariants and off-ladderalleles may provide significant problems, and may be completely missed,when using analysis methods such as oligonucleotide hybridizationarrays, which utilize oligonucleotide probes specific for certain knownalleles. Furthermore, off-ladder alleles and microvariants encounteredwith STR analysis, even when correctly typed, may lead to improperstatistical analysis, since their frequencies in the population aregenerally unknown or poorly characterized, and therefore the statisticalsignificance of a matching genotype may be questionable. All theseadvantages of SNP analysis are considerable in light of the consequencesof most DNA identification cases, which may lead to life imprisonmentfor an individual, or re-association of remains to the family of adeceased individual.

DNA can be isolated from biological samples such as blood, bone, hair,saliva, or semen, and compared with the DNA from a reference source atparticular SNP positions. Multiple SNP markers can be assayedsimultaneously in order to increase the power of discrimination and thestatistical significance of a matching genotype. For example,oligonucleotide arrays can be used to genotype a large number of SNPssimultaneously. The SNPs provided by the present invention can beassayed in combination with other polymorphic genetic markers, such asother SNPs known in the art or STRs, in order to identify an individualor to associate an individual with a particular biological sample.

Furthermore, the SNPs provided by the present invention can be genotypedfor inclusion in a database of DNA genotypes, for example, a criminalDNA databank such as the FBI's Combined DNA Index System (CODIS)database. A genotype obtained from a biological sample of unknown sourcecan then be queried against the database to find a matching genotype,with the SNPs of the present invention providing nucleotide positions atwhich to compare the known and unknown DNA sequences for identity.Accordingly, the present invention provides a database comprising novelSNPs or SNP alleles of the present invention (e.g., the database cancomprise information indicating which alleles are possessed byindividual members of a population at one or more novel SNP sites of thepresent invention), such as for use in forensics, biometrics, or otherhuman identification applications. Such a database typically comprises acomputer-based system in which the SNPs or SNP alleles of the presentinvention are recorded on a computer readable medium (see the section ofthe present specification entitled “Computer-Related Embodiments”).

The SNPs of the present invention can also be assayed for use inpaternity testing. The object of paternity testing is usually todetermine whether a male is the father of a child. In most cases, themother of the child is known and thus, the mother's contribution to thechild's genotype can be traced. Paternity testing investigates whetherthe part of the child's genotype not attributable to the mother isconsistent with that of the putative father. Paternity testing can beperformed by analyzing sets of polymorphisms in the putative father andthe child, with the SNPs of the present invention providing nucleotidepositions at which to compare the putative father's and child's DNAsequences for identity. If the set of polymorphisms in the childattributable to the father does not match the set of polymorphisms ofthe putative father, it can be concluded, barring experimental error,that the putative father is not the father of the child. If the set ofpolymorphisms in the child attributable to the father match the set ofpolymorphisms of the putative father, a statistical calculation can beperformed to determine the probability of coincidental match, and aconclusion drawn as to the likelihood that the putative father is thetrue biological father of the child.

In addition to paternity testing, SNPs are also useful for other typesof kinship testing, such as for verifying familial relationships forimmigration purposes, or for cases in which an individual alleges to berelated to a deceased individual in order to claim an inheritance fromthe deceased individual, etc. For further information regarding theutility of SNPs for paternity testing and other types of kinshiptesting, including methods for statistical analysis, see Krawczak,“Informativity assessment for biallelic single nucleotidepolymorphisms”, Electrophoresis 1999 June; 20(8):1676-81.

The use of the SNPs of the present invention for human identificationfurther extends to various authentication systems, commonly referred toas biometric systems, which typically convert physical characteristicsof humans (or other organisms) into digital data. Biometric systemsinclude various technological devices that measure such uniqueanatomical or physiological characteristics as finger, thumb, or palmprints; hand geometry; vein patterning on the back of the hand; bloodvessel patterning of the retina and color and texture of the iris;facial characteristics; voice patterns; signature and typing dynamics;and DNA. Such physiological measurements can be used to verify identityand, for example, restrict or allow access based on the identification.Examples of applications for biometrics include physical area security,computer and network security, aircraft passenger check-in and boarding,financial transactions, medical records access, government benefitdistribution, voting, law enforcement, passports, visas and immigration,prisons, various military applications, and for restricting access toexpensive or dangerous items, such as automobiles or guns (see, forexample, O'Connor, Stanford Technology Law Review and U.S. Pat. No.6,119,096).

Groups of SNPs, particularly the SNPs provided by the present invention,can be typed to uniquely identify an individual for biometricapplications such as those described above. Such SNP typing can readilybe accomplished using, for example, DNA chips/arrays. Preferably, aminimally invasive means for obtaining a DNA sample is utilized. Forexample, PCR amplification enables sufficient quantities of DNA foranalysis to be obtained from buccal swabs or fingerprints, which containDNA-containing skin cells and oils that are naturally transferred duringcontact. Further information regarding techniques for using SNPs inforensic/human identification applications can be found in, for example,Current Protocols in Human Genetics, John Wiley & Sons, N.Y. (2002),14.1-14.7.

Variant Proteins, Antibodies, Vectors & Host Cells, & Uses Thereof

Variant Proteins Encoded by SNP-Containing Nucleic Acid Molecules

The present invention provides SNP-containing nucleic acid molecules,many of which encode proteins having variant amino acid sequences ascompared to the art-known (i.e., wild-type) proteins. Amino acidsequences encoded by the polymorphic nucleic acid molecules of thepresent invention are provided as SEQ ID NOS:3-4 in Table 1 and theSequence Listing. These variants will generally be referred to herein asvariant proteins/peptides/polypeptides, or polymorphicproteins/peptides/polypeptides of the present invention. The terms“protein”, “peptide”, and “polypeptide” are used herein interchangeably.

A variant protein of the present invention may be encoded by, forexample, a nonsynonymous nucleotide substitution at any one of the cSNPpositions disclosed herein. In addition, variant proteins may alsoinclude proteins whose expression, structure, and/or function is alteredby a SNP disclosed herein, such as a SNP that creates or destroys a stopcodon, a SNP that affects splicing, and a SNP in control/regulatoryelements, e.g. promoters, enhancers, or transcription factor bindingdomains.

As used herein, a protein or peptide is said to be “isolated” or“purified” when it is substantially free of cellular material orchemical precursors or other chemicals. The variant proteins of thepresent invention can be purified to homogeneity or other lower degreesof purity. The level of purification will be based on the intended use.The key feature is that the preparation allows for the desired functionof the variant protein, even if in the presence of considerable amountsof other components.

As used herein, “substantially free of cellular material” includespreparations of the variant protein having less than about 30% (by dryweight) other proteins (i.e., contaminating protein), less than about20% other proteins, less than about 10% other proteins, or less thanabout 5% other proteins. When the variant protein is recombinantlyproduced, it can also be substantially free of culture medium, i.e.,culture medium represents less than about 20% of the volume of theprotein preparation. The language “substantially free of chemicalprecursors or other chemicals” includes preparations of the variantprotein in which it is separated from chemical precursors or otherchemicals that are involved in its synthesis. In one embodiment, thelanguage “substantially free of chemical precursors or other chemicals”includes preparations of the variant protein having less than about 30%(by dry weight) chemical precursors or other chemicals, less than about20% chemical precursors or other chemicals, less than about 10% chemicalprecursors or other chemicals, or less than about 5% chemical precursorsor other chemicals.

An isolated variant protein may be purified from cells that naturallyexpress it, purified from cells that have been altered to express it(recombinant host cells), or synthesized using known protein synthesismethods. For example, a nucleic acid molecule containing SNP(s) encodingthe variant protein can be cloned into an expression vector, theexpression vector introduced into a host cell, and the variant proteinexpressed in the host cell. The variant protein can then be isolatedfrom the cells by any appropriate purification scheme using standardprotein purification techniques. Examples of these techniques aredescribed in detail below (Sambrook and Russell, 2000, MolecularCloning: A Laboratory Manual, Cold Spring Harbor Laboratory Press, ColdSpring Harbor, N.Y.).

The present invention provides isolated variant proteins that comprise,consist of or consist essentially of amino acid sequences that containone or more variant amino acids encoded by one or more codons whichcontain a SNP of the present invention.

Accordingly, the present invention provides variant proteins thatconsist of amino acid sequences that contain one or more amino acidpolymorphisms (or truncations or extensions due to creation ordestruction of a stop codon, respectively) encoded by the SNPs providedin Table 1 and/or Table 2. A protein consists of an amino acid sequencewhen the amino acid sequence is the entire amino acid sequence of theprotein.

The present invention further provides variant proteins that consistessentially of amino acid sequences that contain one or more amino acidpolymorphisms (or truncations or extensions due to creation ordestruction of a stop codon, respectively) encoded by the SNPs providedin Table 1 and/or Table 2. A protein consists essentially of an aminoacid sequence when such an amino acid sequence is present with only afew additional amino acid residues in the final protein.

The present invention further provides variant proteins that compriseamino acid sequences that contain one or more amino acid polymorphisms(or truncations or extensions due to creation or destruction of a stopcodon, respectively) encoded by the SNPs provided in Table 1 and/orTable 2. A protein comprises an amino acid sequence when the amino acidsequence is at least part of the final amino acid sequence of theprotein. In such a fashion, the protein may contain only the variantamino acid sequence or have additional amino acid residues, such as acontiguous encoded sequence that is naturally associated with it orheterologous amino acid residues. Such a protein can have a fewadditional amino acid residues or can comprise many more additionalamino acids. A brief description of how various types of these proteinscan be made and isolated is provided below.

The variant proteins of the present invention can be attached toheterologous sequences to form chimeric or fusion proteins. Suchchimeric and fusion proteins comprise a variant protein operativelylinked to a heterologous protein having an amino acid sequence notsubstantially homologous to the variant protein. “Operatively linked”indicates that the coding sequences for the variant protein and theheterologous protein are ligated in-frame. The heterologous protein canbe fused to the N-terminus or C-terminus of the variant protein. Inanother embodiment, the fusion protein is encoded by a fusionpolynucleotide that is synthesized by conventional techniques includingautomated DNA synthesizers. Alternatively, PCR amplification of genefragments can be carried out using anchor primers which give rise tocomplementary overhangs between two consecutive gene fragments which cansubsequently be annealed and re-amplified to generate a chimeric genesequence (see Ausubel et al., Current Protocols in Molecular Biology,1992). Moreover, many expression vectors are commercially available thatalready encode a fusion moiety (e.g., a GST protein). A variantprotein-encoding nucleic acid can be cloned into such an expressionvector such that the fusion moiety is linked in-frame to the variantprotein.

In many uses, the fusion protein does not affect the activity of thevariant protein. The fusion protein can include, but is not limited to,enzymatic fusion proteins, for example, beta-galactosidase fusions,yeast two-hybrid GAL fusions, poly-His fusions, MYC-tagged, HI-taggedand Ig fusions. Such fusion proteins, particularly poly-His fusions, canfacilitate their purification following recombinant expression. Incertain host cells (e g, mammalian host cells), expression and/orsecretion of a protein can be increased by using a heterologous signalsequence. Fusion proteins are further described in, for example, Terpe,“Overview of tag protein fusions: from molecular and biochemicalfundamentals to commercial systems”, Appl Microbiol Biotechnol. 2003January; 60(5):523-33. Epub 2002 Nov. 7; Graddis et al., “Designingproteins that work using recombinant technologies”, Curr PharmBiotechnol. 2002 December; 3(4):285-97; and Nilsson et al., “Affinityfusion strategies for detection, purification, and immobilization ofrecombinant proteins”, Protein Expr Purif. 1997 October; 11(1):1-16.

The present invention also relates to further obvious variants of thevariant polypeptides of the present invention, such asnaturally-occurring mature forms (e.g., alleleic variants),non-naturally occurring recombinantly-derived variants, and orthologsand paralogs of such proteins that share sequence homology. Suchvariants can readily be generated using art-known techniques in thefields of recombinant nucleic acid technology and protein biochemistry.It is understood, however, that variants exclude those known in theprior art before the present invention.

Further variants of the variant polypeptides disclosed in Table 1 cancomprise an amino acid sequence that shares at least 70-80%, 80-85%,85-90%, 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, or 99% sequence identitywith an amino acid sequence disclosed in Table 1 (or a fragment thereof)and that includes a novel amino acid residue (allele) disclosed in Table1 (which is encoded by a novel SNP allele). Thus, an aspect of thepresent invention that is specifically contemplated are polypeptidesthat have a certain degree of sequence variation compared with thepolypeptide sequences shown in Table 1, but that contain a novel aminoacid residue (allele) encoded by a novel SNP allele disclosed herein. Inother words, as long as a polypeptide contains a novel amino acidresidue disclosed herein, other portions of the polypeptide that flankthe novel amino acid residue can vary to some degree from thepolypeptide sequences shown in Table 1.

Full-length pre-processed forms, as well as mature processed forms, ofproteins that comprise one of the amino acid sequences disclosed hereincan readily be identified as having complete sequence identity to one ofthe variant proteins of the present invention as well as being encodedby the same genetic locus as the variant proteins provided herein.

Orthologs of a variant peptide can readily be identified as having somedegree of significant sequence homology/identity to at least a portionof a variant peptide as well as being encoded by a gene from anotherorganism. Preferred orthologs will be isolated from non-human mammals,preferably primates, for the development of human therapeutic targetsand agents. Such orthologs can be encoded by a nucleic acid sequencethat hybridizes to a variant peptide-encoding nucleic acid moleculeunder moderate to stringent conditions depending on the degree ofrelatedness of the two organisms yielding the homologous proteins.

Variant proteins include, but are not limited to, proteins containingdeletions, additions and substitutions in the amino acid sequence causedby the SNPs of the present invention. One class of substitutions isconserved amino acid substitutions in which a given amino acid in apolypeptide is substituted for another amino acid of likecharacteristics. Typical conservative substitutions are replacements,one for another, among the aliphatic amino acids Ala, Val, Leu, and Ile;interchange of the hydroxyl residues Ser and Thr; exchange of the acidicresidues Asp and Glu; substitution between the amide residues Asn andGln; exchange of the basic residues Lys and Arg; and replacements amongthe aromatic residues Phe and Tyr. Guidance concerning which amino acidchanges are likely to be phenotypically silent are found in, forexample, Bowie et al., Science 247:1306-1310 (1990).

Variant proteins can be fully functional or can lack function in one ormore activities, e.g. ability to bind another molecule, ability tocatalyze a substrate, ability to mediate signaling, etc. Fullyfunctional variants typically contain only conservative variations orvariations in non-critical residues or in non-critical regions.Functional variants can also contain substitution of similar amino acidsthat result in no change or an insignificant change in function.Alternatively, such substitutions may positively or negatively affectfunction to some degree. Non-functional variants typically contain oneor more non-conservative amino acid substitutions, deletions,insertions, inversions, truncations or extensions, or a substitution,insertion, inversion, or deletion of a critical residue or in a criticalregion.

Amino acids that are essential for function of a protein can beidentified by methods known in the art, such as site-directedmutagenesis or alanine-scanning mutagenesis (Cunningham et al., Science244:1081-1085 (1989)), particularly using the amino acid sequence andpolymorphism information provided in Table 1. The latter procedureintroduces single alanine mutations at every residue in the molecule.The resulting mutant molecules are then tested for biological activitysuch as enzyme activity or in assays such as an in vitro proliferativeactivity. Sites that are critical for binding partner/substrate bindingcan also be determined by structural analysis such as crystallization,nuclear magnetic resonance or photoaffinity labeling (Smith et al., J.Mol. Biol. 224:899-904 (1992); de Vos et al. Science 255:306-312(1992)).

Polypeptides can contain amino acids other than the 20 amino acidscommonly referred to as the 20 naturally occurring amino acids. Further,many amino acids, including the terminal amino acids, may be modified bynatural processes, such as processing and other post-translationalmodifications, or by chemical modification techniques well known in theart. Accordingly, the variant proteins of the present invention alsoencompass derivatives or analogs in which a substituted amino acidresidue is not one encoded by the genetic code, in which a substituentgroup is included, in which the mature polypeptide is fused with anothercompound, such as a compound to increase the half-life of thepolypeptide (e.g., polyethylene glycol), or in which additional aminoacids are fused to the mature polypeptide, such as a leader or secretorysequence or a sequence for purification of the mature polypeptide or apro-protein sequence.

Known protein modifications include, but are not limited to,acetylation, acylation, ADP-ribosylation, amidation, covalent attachmentof flavin, covalent attachment of a heme moiety, covalent attachment ofa nucleotide or nucleotide derivative, covalent attachment of a lipid orlipid derivative, covalent attachment of phosphotidylinositol,cross-linking, cyclization, disulfide bond formation, demethylation,formation of covalent crosslinks, formation of cystine, formation ofpyroglutamate, formylation, gamma carboxylation, glycosylation, GPIanchor formation, hydroxylation, iodination, methylation,myristoylation, oxidation, proteolytic processing, phosphorylation,prenylation, racemization, selenoylation, sulfation, transfer-RNAmediated addition of amino acids to proteins such as arginylation, andubiquitination.

Such protein modifications are well known to those of skill in the artand have been described in great detail in the scientific literature.Several particularly common modifications, glycosylation, lipidattachment, sulfation, gamma-carboxylation of glutamic acid residues,hydroxylation and ADP-ribosylation, for instance, are described in mostbasic texts, such as Proteins—Structure and Molecular Properties, 2ndEd., T. E. Creighton, W. H. Freeman and Company, New York (1993); Wold,F., Posttranslational Covalent Modification of Proteins, B. C. Johnson,Ed., Academic Press, New York 1-12 (1983); Seifter et al., Meth.Enzymol. 182: 626-646 (1990); and Rattan et A, Ann. N.Y. Acad. Sci.663:48-62 (1992).

The present invention further provides fragments of the variant proteinsin which the fragments contain one or more amino acid sequencevariations (e.g., substitutions, or truncations or extensions due tocreation or destruction of a stop codon) encoded by one or more SNPsdisclosed herein. The fragments to which the invention pertains,however, are not to be construed as encompassing fragments that havebeen disclosed in the prior art before the present invention.

As used herein, a fragment may comprise at least about 4, 8, 10, 12, 14,16, 18, 20, 25, 30, 50, 100 (or any other number in-between) or morecontiguous amino acid residues from a variant protein, wherein at leastone amino acid residue is affected by a SNP of the present invention,e.g., a variant amino acid residue encoded by a nonsynonymous nucleotidesubstitution at a cSNP position provided by the present invention. Thevariant amino acid encoded by a cSNP may occupy any residue positionalong the sequence of the fragment. Such fragments can be chosen basedon the ability to retain one or more of the biological activities of thevariant protein or the ability to perform a function, e.g., act as animmunogen. Particularly important fragments are biologically activefragments. Such fragments will typically comprise a domain or motif of avariant protein of the present invention, e.g., active site,transmembrane domain, or ligand/substrate binding domain. Otherfragments include, but are not limited to, domain or motif-containingfragments, soluble peptide fragments, and fragments containingimmunogenic structures. Predicted domains and functional sites arereadily identifiable by computer programs well known to those of skillin the art (e.g., PROSITE analysis) (Current Protocols in ProteinScience, John Wiley & Sons, N.Y. (2002)).

Uses of Variant Proteins

The variant proteins of the present invention can be used in a varietyof ways, including but not limited to, in assays to determine thebiological activity of a variant protein, such as in a panel of multipleproteins for high-throughput screening; to raise antibodies or to elicitanother type of immune response; as a reagent (including the labeledreagent) in assays designed to quantitatively determine levels of thevariant protein (or its binding partner) in biological fluids; as amarker for cells or tissues in which it is preferentially expressed(either constitutively or at a particular stage of tissuedifferentiation or development or in a disease state); as a target forscreening for a therapeutic agent; and as a direct therapeutic agent tobe administered into a human subject. Any of the variant proteinsdisclosed herein may be developed into reagent grade or kit format forcommercialization as research products. Methods for performing the useslisted above are well known to those skilled in the art (see, e.g.,Molecular Cloning: A Laboratory Manual, Cold Spring Harbor LaboratoryPress, Sambrook and Russell, 2000, and Methods in Enzymology: Guide toMolecular Cloning Techniques, Academic Press, Berger, S. L. and A. R.Kimmel eds., 1987).

In a specific embodiment of the invention, the methods of the presentinvention include detection of one or more variant proteins disclosedherein. Variant proteins are disclosed in Table 1 and in the SequenceListing as SEQ ID NOS:3-4. Detection of such proteins can beaccomplished using, for example, antibodies, small molecule compounds,aptamers, ligands/substrates, other proteins or protein fragments, orother protein-binding agents. Preferably, protein detection agents arespecific for a variant protein of the present invention and cantherefore discriminate between a variant protein of the presentinvention and the wild-type protein or another variant form. This cangenerally be accomplished by, for example, selecting or designingdetection agents that bind to the region of a protein that differsbetween the variant and wild-type protein, such as a region of a proteinthat contains one or more amino acid substitutions that is/are encodedby a non-synonymous cSNP of the present invention, or a region of aprotein that follows a nonsense mutation-type SNP that creates a stopcodon thereby leading to a shorter polypeptide, or a region of a proteinthat follows a read-through mutation-type SNP that destroys a stop codonthereby leading to a longer polypeptide in which a portion of thepolypeptide is present in one version of the polypeptide but not theother.

In another specific aspect of the invention, the variant proteins of thepresent invention are used as targets for diagnosing psoriasis or fordetermining predisposition to psoriasis in a human. Accordingly, theinvention provides methods for detecting the presence of, or levels of,one or more variant proteins of the present invention in a cell, tissue,or organism. Such methods typically involve contacting a test samplewith an agent (e.g., an antibody, small molecule compound, or peptide)capable of interacting with the variant protein such that specificbinding of the agent to the variant protein can be detected. Such anassay can be provided in a single detection format or a multi-detectionformat such as an array, for example, an antibody or aptamer array(arrays for protein detection may also be referred to as “proteinchips”). The variant protein of interest can be isolated from a testsample and assayed for the presence of a variant amino acid sequenceencoded by one or more SNPs disclosed by the present invention. The SNPsmay cause changes to the protein and the corresponding proteinfunction/activity, such as through non-synonymous substitutions inprotein coding regions that can lead to amino acid substitutions,deletions, insertions, and/or rearrangements; formation or destructionof stop codons; or alteration of control elements such as promoters.SNPs may also cause inappropriate post-translational modifications.

One preferred agent for detecting a variant protein in a sample is anantibody capable of selectively binding to a variant form of the protein(antibodies are described in greater detail in the next section). Suchsamples include, for example, tissues, cells, and biological fluidsisolated from a subject, as well as tissues, cells and fluids presentwithin a subject.

In vitro methods for detection of the variant proteins associated withpsoriasis that are disclosed herein and fragments thereof include, butare not limited to, enzyme linked immunosorbent assays (ELISAs),radioimmunoassays (RIA), Western blots, immunoprecipitations,immunofluorescence, and protein arrays/chips (e.g., arrays of antibodiesor aptamers). For further information regarding immunoassays and relatedprotein detection methods, see Current Protocols in Immunology, JohnWiley & Sons, N.Y., and Hage, “Immunoassays”, Anal Chem. 1999 Jun. 15;71(12):294R-304R.

Additional analytic methods of detecting amino acid variants include,but are not limited to, altered electrophoretic mobility, alteredtryptic peptide digest, altered protein activity in cell-based orcell-free assay, alteration in ligand or antibody-binding pattern,altered isoelectric point, and direct amino acid sequencing.

Alternatively, variant proteins can be detected in vivo in a subject byintroducing into the subject a labeled antibody (or other type ofdetection reagent) specific for a variant protein. For example, theantibody can be labeled with a radioactive marker whose presence andlocation in a subject can be detected by standard imaging techniques.

Other uses of the variant peptides of the present invention are based onthe class or action of the protein. For example, proteins isolated fromhumans and their mammalian orthologs serve as targets for identifyingagents (e.g., small molecule drugs or antibodies) for use in therapeuticapplications, particularly for modulating a biological or pathologicalresponse in a cell or tissue that expresses the protein. Pharmaceuticalagents can be developed that modulate protein activity.

As an alternative to modulating gene expression, therapeutic compoundscan be developed that modulate protein function. For example, many SNPsdisclosed herein affect the amino acid sequence of the encoded protein(e.g., non-synonymous cSNPs and nonsense mutation-type SNPs). Suchalterations in the encoded amino acid sequence may affect proteinfunction, particularly if such amino acid sequence variations occur infunctional protein domains, such as catalytic domains, ATP-bindingdomains, or ligand/substrate binding domains. It is well established inthe art that variant proteins having amino acid sequence variations infunctional domains can cause or influence pathological conditions. Insuch instances, compounds (e.g., small molecule drugs or antibodies) canbe developed that target the variant protein and modulate (e.g., up- ordown-regulate) protein function/activity.

The therapeutic methods of the present invention further include methodsthat target one or more variant proteins of the present invention.Variant proteins can be targeted using, for example, small moleculecompounds, antibodies, aptamers, ligands/substrates, other proteins, orother protein-binding agents. Additionally, the skilled artisan willrecognize that the novel protein variants (and polymorphic nucleic acidmolecules) disclosed in Table 1 may themselves be directly used astherapeutic agents by acting as competitive inhibitors of correspondingart-known proteins (or nucleic acid molecules such as mRNA molecules).

The variant proteins of the present invention are particularly useful indrug screening assays, in cell-based or cell-free systems. Cell-basedsystems can utilize cells that naturally express the protein, a biopsyspecimen, or cell cultures. In one embodiment, cell-based assays involverecombinant host cells expressing the variant protein. Cell-free assayscan be used to detect the ability of a compound to directly bind to avariant protein or to the corresponding SNP-containing nucleic acidfragment that encodes the variant protein.

A variant protein of the present invention, as well as appropriatefragments thereof, can be used in high-throughput screening assays totest candidate compounds for the ability to bind and/or modulate theactivity of the variant protein. These candidate compounds can befurther screened against a protein having normal function (e.g., awild-type/non-variant protein) to further determine the effect of thecompound on the protein activity. Furthermore, these compounds can betested in animal or invertebrate systems to determine in vivoactivity/effectiveness. Compounds can be identified that activate(agonists) or inactivate (antagonists) the variant protein, anddifferent compounds can be identified that cause various degrees ofactivation or inactivation of the variant protein.

Further, the variant proteins can be used to screen a compound for theability to stimulate or inhibit interaction between the variant proteinand a target molecule that normally interacts with the protein. Thetarget can be a ligand, a substrate or a binding partner that theprotein normally interacts with (for example, epinephrine ornorepinephrine). Such assays typically include the steps of combiningthe variant protein with a candidate compound under conditions thatallow the variant protein, or fragment thereof, to interact with thetarget molecule, and to detect the formation of a complex between theprotein and the target or to detect the biochemical consequence of theinteraction with the variant protein and the target, such as any of theassociated effects of signal transduction.

Candidate compounds include, for example, 1) peptides such as solublepeptides, including Ig-tailed fusion peptides and members of randompeptide libraries (see, e.g., Lam et al., Nature 354:82-84 (1991);Houghten et al., Nature 354:84-86 (1991)) and combinatorialchemistry-derived molecular libraries made of D- and/or L-configurationamino acids; 2) phosphopeptides (e.g., members of random and partiallydegenerate, directed phosphopeptide libraries, see, e.g., Songyang etal., Cell 72:767-778 (1993)); 3) antibodies (e.g., polyclonal,monoclonal, humanized, anti-idiotypic, chimeric, and single chainantibodies as well as Fab, F(ab′)2, Fab expression library fragments,and epitope-binding fragments of antibodies); and 4) small organic andinorganic molecules (e.g., molecules obtained from combinatorial andnatural product libraries).

One candidate compound is a soluble fragment of the variant protein thatcompetes for ligand binding. Other candidate compounds include mutantproteins or appropriate fragments containing mutations that affectvariant protein function and thus compete for ligand. Accordingly, afragment that competes for ligand, for example with a higher affinity,or a fragment that binds ligand but does not allow release, isencompassed by the invention.

The invention further includes other end point assays to identifycompounds that modulate (stimulate or inhibit) variant protein activity.The assays typically involve an assay of events in the signaltransduction pathway that indicate protein activity. Thus, theexpression of genes that are up or down-regulated in response to thevariant protein dependent signal cascade can be assayed. In oneembodiment, the regulatory region of such genes can be operably linkedto a marker that is easily detectable, such as luciferase.Alternatively, phosphorylation of the variant protein, or a variantprotein target, could also be measured. Any of the biological orbiochemical functions mediated by the variant protein can be used as anendpoint assay. These include all of the biochemical or biologicalevents described herein, in the references cited herein, incorporated byreference for these endpoint assay targets, and other functions known tothose of ordinary skill in the art.

Binding and/or activating compounds can also be screened by usingchimeric variant proteins in which an amino terminal extracellulardomain or parts thereof, an entire transmembrane domain or subregions,and/or the carboxyl terminal intracellular domain or parts thereof, canbe replaced by heterologous domains or subregions. For example, asubstrate-binding region can be used that interacts with a differentsubstrate than that which is normally recognized by a variant protein.Accordingly, a different set of signal transduction components isavailable as an end-point assay for activation. This allows for assaysto be performed in other than the specific host cell from which thevariant protein is derived.

The variant proteins are also useful in competition binding assays inmethods designed to discover compounds that interact with the variantprotein. Thus, a compound can be exposed to a variant protein underconditions that allow the compound to bind or to otherwise interact withthe variant protein. A binding partner, such as ligand, that normallyinteracts with the variant protein is also added to the mixture. If thetest compound interacts with the variant protein or its binding partner,it decreases the amount of complex formed or activity from the variantprotein. This type of assay is particularly useful in screening forcompounds that interact with specific regions of the variant protein(Hodgson, Bio/technology, 1992, Sep. 10(9), 973-80).

To perform cell-free drug screening assays, it is sometimes desirable toimmobilize either the variant protein or a fragment thereof, or itstarget molecule, to facilitate separation of complexes from uncomplexedforms of one or both of the proteins, as well as to accommodateautomation of the assay.

Any method for immobilizing proteins on matrices can be used in drugscreening assays. In one embodiment, a fusion protein containing anadded domain allows the protein to be bound to a matrix. For example,glutathione-S-transferase/¹²⁵I fusion proteins can be adsorbed ontoglutathione sepharose beads (Sigma Chemical, St. Louis, Mo.) orglutathione derivatized microtitre plates, which are then combined withthe cell lysates (e.g., ³⁵S-labeled) and a candidate compound, such as adrug candidate, and the mixture incubated under conditions conducive tocomplex formation (e.g., at physiological conditions for salt and pH).Following incubation, the beads can be washed to remove any unboundlabel, and the matrix immobilized and radiolabel determined directly, orin the supernatant after the complexes are dissociated. Alternatively,the complexes can be dissociated from the matrix, separated by SDS-PAGE,and the level of bound material found in the bead fraction quantitatedfrom the gel using standard electrophoretic techniques.

Either the variant protein or its target molecule can be immobilizedutilizing conjugation of biotin and streptavidin. Alternatively,antibodies reactive with the variant protein but which do not interferewith binding of the variant protein to its target molecule can bederivatized to the wells of the plate, and the variant protein trappedin the wells by antibody conjugation. Preparations of the targetmolecule and a candidate compound are incubated in the variantprotein-presenting wells and the amount of complex trapped in the wellcan be quantitated. Methods for detecting such complexes, in addition tothose described above for the GST-immobilized complexes, includeimmunodetection of complexes using antibodies reactive with the proteintarget molecule, or which are reactive with variant protein and competewith the target molecule, and enzyme-linked assays that rely ondetecting an enzymatic activity associated with the target molecule.

Modulators of variant protein activity identified according to thesedrug screening assays can be used to treat a subject with a disordermediated by the protein pathway, such as psoriasis. These methods oftreatment typically include the steps of administering the modulators ofprotein activity in a pharmaceutical composition to a subject in need ofsuch treatment.

The variant proteins, or fragments thereof, disclosed herein canthemselves be directly used to treat a disorder characterized by anabsence of, inappropriate, or unwanted expression or activity of thevariant protein. Accordingly, methods for treatment include the use of avariant protein disclosed herein or fragments thereof.

In yet another aspect of the invention, variant proteins can be used as“bait proteins” in a two-hybrid assay or three-hybrid assay (see, e.g.,U.S. Pat. No. 5,283,317; Zervos et al. (1993) Cell 72:223-232; Madura etal. (1993) J. Biol. Chem. 268:12046-12054; Bartel et al. (1993)Biotechniques 14:920-924; Iwabuchi et al. (1993) Oncogene 8:1693-1696;and Brent WO94/10300) to identify other proteins that bind to orinteract with the variant protein and are involved in variant proteinactivity. Such variant protein-binding proteins are also likely to beinvolved in the propagation of signals by the variant proteins orvariant protein targets as, for example, elements of a protein-mediatedsignaling pathway. Alternatively, such variant protein-binding proteinsare inhibitors of the variant protein.

The two-hybrid system is based on the modular nature of mosttranscription factors, which typically consist of separable DNA-bindingand activation domains. Briefly, the assay typically utilizes twodifferent DNA constructs. In one construct, the gene that codes for avariant protein is fused to a gene encoding the DNA binding domain of aknown transcription factor (e.g., GAL-4). In the other construct, a DNAsequence, from a library of DNA sequences, that encodes an unidentifiedprotein (“prey” or “sample”) is fused to a gene that codes for theactivation domain of the known transcription factor. If the “bait” andthe “prey” proteins are able to interact, in vivo, forming a variantprotein-dependent complex, the DNA-binding and activation domains of thetranscription factor are brought into close proximity. This proximityallows transcription of a reporter gene (e.g., LacZ) that is operablylinked to a transcriptional regulatory site responsive to thetranscription factor. Expression of the reporter gene can be detected,and cell colonies containing the functional transcription factor can beisolated and used to obtain the cloned gene that encodes the proteinthat interacts with the variant protein.

Antibodies Directed to Variant Proteins

The present invention also provides antibodies that selectively bind tothe variant proteins disclosed herein and fragments thereof. Suchantibodies may be used to quantitatively or qualitatively detect thevariant proteins of the present invention. As used herein, an antibodyselectively binds a target variant protein when it binds the variantprotein and does not significantly bind to non-variant proteins, i.e.,the antibody does not significantly bind to normal, wild-type, orart-known proteins that do not contain a variant amino acid sequence dueto one or more SNPs of the present invention (variant amino acidsequences may be due to, for example, nonsynonymous cSNPs, nonsense SNPsthat create a stop codon, thereby causing a truncation of a polypeptideor SNPs that cause read-through mutations resulting in an extension of apolypeptide).

As used herein, an antibody is defined in terms consistent with thatrecognized in the art: they are multi-subunit proteins produced by anorganism in response to an antigen challenge. The antibodies of thepresent invention include both monoclonal antibodies and polyclonalantibodies, as well as antigen-reactive proteolytic fragments of suchantibodies, such as Fab, F(ab)′₂, and Fv fragments. In addition, anantibody of the present invention further includes any of a variety ofengineered antigen-binding molecules such as a chimeric antibody (U.S.Pat. Nos. 4,816,567 and 4,816,397; Morrison et al., Proc. Natl. Acad.Sci. USA, 81:6851, 1984; Neuberger et al., Nature 312:604, 1984), ahumanized antibody (U.S. Pat. Nos. 5,693,762; 5,585,089; and 5,565,332),a single-chain Fv (U.S. Pat. No. 4,946,778; Ward et al., Nature 334:544,1989), a bispecific antibody with two binding specificities (Segal etal., J. Immunol. Methods 248:1, 2001; Carter, J. Immunol. Methods 248:7,2001), a diabody, a triabody, and a tetrabody (Todorovska et al., J.Immunol. Methods, 248:47, 2001), as well as a Fab conjugate (dimer ortrimer), and a minibody.

Many methods are known in the art for generating and/or identifyingantibodies to a given target antigen (Harlow, Antibodies, Cold SpringHarbor Press, (1989)). In general, an isolated peptide (e.g., a variantprotein of the present invention) is used as an immunogen and isadministered to a mammalian organism, such as a rat, rabbit, hamster ormouse. Either a full-length protein, an antigenic peptide fragment(e.g., a peptide fragment containing a region that varies between avariant protein and a corresponding wild-type protein), or a fusionprotein can be used. A protein used as an immunogen may benaturally-occurring, synthetic or recombinantly produced, and may beadministered in combination with an adjuvant, including but not limitedto, Freund's (complete and incomplete), mineral gels such as aluminumhydroxide, surface active substance such as lysolecithin, pluronicpolyols, polyanions, peptides, oil emulsions, keyhole limpet hemocyanin,dinitrophenol, and the like.

Monoclonal antibodies can be produced by hybridoma technology (Kohlerand Milstein, Nature, 256:495, 1975), which immortalizes cells secretinga specific monoclonal antibody. The immortalized cell lines can becreated in vitro by fusing two different cell types, typicallylymphocytes, and tumor cells. The hybridoma cells may be cultivated invitro or in vivo. Additionally, fully human antibodies can be generatedby transgenic animals (He et al., J. Immunol., 169:595, 2002). Fd phageand Fd phagemid technologies may be used to generate and selectrecombinant antibodies in vitro (Hoogenboom and Chames, Immunol. Today21:371, 2000; Liu et al., J. Mol. Biol. 315:1063, 2002). Thecomplementarity-determining regions of an antibody can be identified,and synthetic peptides corresponding to such regions may be used tomediate antigen binding (U.S. Pat. No. 5,637,677).

Antibodies are preferably prepared against regions or discrete fragmentsof a variant protein containing a variant amino acid sequence ascompared to the corresponding wild-type protein (e.g., a region of avariant protein that includes an amino acid encoded by a nonsynonymouscSNP, a region affected by truncation caused by a nonsense SNP thatcreates a stop codon, or a region resulting from the destruction of astop codon due to read-through mutation caused by a SNP). Furthermore,preferred regions will include those involved in function/activityand/or protein/binding partner interaction. Such fragments can beselected on a physical property, such as fragments corresponding toregions that are located on the surface of the protein, e.g.,hydrophilic regions, or can be selected based on sequence uniqueness, orbased on the position of the variant amino acid residue(s) encoded bythe SNPs provided by the present invention. An antigenic fragment willtypically comprise at least about 8-10 contiguous amino acid residues inwhich at least one of the amino acid residues is an amino acid affectedby a SNP disclosed herein. The antigenic peptide can comprise, however,at least 12, 14, 16, 20, 25, 50, 100 (or any other number in-between) ormore amino acid residues, provided that at least one amino acid isaffected by a SNP disclosed herein.

Detection of an antibody of the present invention can be facilitated bycoupling (i.e., physically linking) the antibody or an antigen-reactivefragment thereof to a detectable substance. Detectable substancesinclude, but are not limited to, various enzymes, prosthetic groups,fluorescent materials, luminescent materials, bioluminescent materials,and radioactive materials. Examples of suitable enzymes includehorseradish peroxidase, alkaline phosphatase, β-galactosidase, oracetylcholinesterase; examples of suitable prosthetic group complexesinclude streptavidin/biotin and avidin/biotin; examples of suitablefluorescent materials include umbelliferone, fluorescein, fluoresceinisothiocyanate, rhodamine, dichlorotriazinylamine fluorescein, dansylchloride or phycoerythrin; an example of a luminescent material includesluminol; examples of bioluminescent materials include luciferase,luciferin, and aequorin, and examples of suitable radioactive materialinclude ¹²⁵I, ¹³¹I, ³⁵S or ³H.

Antibodies, particularly the use of antibodies as therapeutic agents,are reviewed in: Morgan, “Antibody therapy for Alzheimer's disease”,Expert Rev Vaccines. 2003 February; 2(1):53-9; Ross et al., “Anticancerantibodies”, Am J Clin Pathol. 2003 April; 119(4):472-85; Goldenberg,“Advancing role of radiolabeled antibodies in the therapy of cancer”,Cancer Immunol Immunother. 2003 May; 52(5):281-96. Epub 2003 Mar. 11;Ross et al., “Antibody-based therapeutics in oncology”, Expert RevAnticancer Ther. 2003 February; 3(1):107-21; Cao et al., “Bispecificantibody conjugates in therapeutics”, Adv Drug Deliv Rev. 2003 Feb. 10;55(2):171-97; von Mehren et al., “Monoclonal antibody therapy forcancer”, Annu Rev Med. 2003; 54:343-69. Epub 2001 Dec. 3; Hudson et al.,“Engineered antibodies”, Nat Med. 2003 January; 9(1):129-34; Brekke etal., “Therapeutic antibodies for human diseases at the dawn of thetwenty-first century”, Nat Rev Drug Discov. 2003 January; 2(1):52-62(Erratum in: Nat Rev Drug Discov. 2003 March; 2(3):240); Houdebine,“Antibody manufacture in transgenic animals and comparisons with othersystems”, Curr Opin Biotechnol. 2002 December; 13(6):625-9; Andreakos etal., “Monoclonal antibodies in immune and inflammatory diseases”, CurrOpin Biotechnol. 2002 December; 13(6):615-20; Kellermann et al.,“Antibody discovery: the use of transgenic mice to generate humanmonoclonal antibodies for therapeutics”, Curr Opin Biotechnol. 2002December; 13(6):593-7; Pini et al., “Phage display and colony filterscreening for high-throughput selection of antibody libraries”, CombChem High Throughput Screen. 2002 November; 5(7):503-10; Batra et al.,“Pharmacokinetics and biodistribution of genetically engineeredantibodies”, Curr Opin Biotechnol. 2002 December; 13(6):603-8; andTangri et al., “Rationally engineered proteins or antibodies with absentor reduced immunogenicity”, Curr Med Chem. 2002 December; 9(24):2191-9.

Uses of Antibodies

Antibodies can be used to isolate the variant proteins of the presentinvention from a natural cell source or from recombinant host cells bystandard techniques, such as affinity chromatography orimmunoprecipitation. In addition, antibodies are useful for detectingthe presence of a variant protein of the present invention in cells ortissues to determine the pattern of expression of the variant proteinamong various tissues in an organism and over the course of normaldevelopment or disease progression. Further, antibodies can be used todetect variant protein in situ, in vitro, in a bodily fluid, or in acell lysate or supernatant in order to evaluate the amount and patternof expression. Also, antibodies can be used to assess abnormal tissuedistribution, abnormal expression during development, or expression inan abnormal condition, such as psoriasis. Additionally, antibodydetection of circulating fragments of the full-length variant proteincan be used to identify turnover.

Antibodies to the variant proteins of the present invention are alsouseful in pharmacogenomic analysis. Thus, antibodies against variantproteins encoded by alternative SNP alleles can be used to identifyindividuals that require modified treatment modalities.

Further, antibodies can be used to assess expression of the variantprotein in disease states such as in active stages of the disease or inan individual with a predisposition to a disease related to theprotein's function, particularly psoriasis. Antibodies specific for avariant protein encoded by a SNP-containing nucleic acid molecule of thepresent invention can be used to assay for the presence of the variantprotein, such as to screen for predisposition to psoriasis as indicatedby the presence of the variant protein.

Antibodies are also useful as diagnostic tools for evaluating thevariant proteins in conjunction with analysis by electrophoreticmobility, isoelectric point, tryptic peptide digest, and other physicalassays well known in the art.

Antibodies are also useful for tissue typing. Thus, where a specificvariant protein has been correlated with expression in a specifictissue, antibodies that are specific for this protein can be used toidentify a tissue type.

Antibodies can also be used to assess aberrant subcellular localizationof a variant protein in cells in various tissues. The diagnostic usescan be applied, not only in genetic testing, but also in monitoring atreatment modality. Accordingly, where treatment is ultimately aimed atcorrecting the expression level or the presence of variant protein oraberrant tissue distribution or developmental expression of a variantprotein, antibodies directed against the variant protein or relevantfragments can be used to monitor therapeutic efficacy.

The antibodies are also useful for inhibiting variant protein function,for example, by blocking the binding of a variant protein to a bindingpartner. These uses can also be applied in a therapeutic context inwhich treatment involves inhibiting a variant protein's function. Anantibody can be used, for example, to block or competitively inhibitbinding, thus modulating (agonizing or antagonizing) the activity of avariant protein. Antibodies can be prepared against specific variantprotein fragments containing sites required for function or against anintact variant protein that is associated with a cell or cell membrane.For in vivo administration, an antibody may be linked with an additionaltherapeutic payload such as a radionuclide, an enzyme, an immunogenicepitope, or a cytotoxic agent. Suitable cytotoxic agents include, butare not limited to, bacterial toxin such as diphtheria, and plant toxinsuch as ricin. The in vivo half-life of an antibody or a fragmentthereof may be lengthened by pegylation through conjugation topolyethylene glycol (Leong et al., Cytokine 16:106, 2001).

The invention also encompasses kits for using antibodies, such as kitsfor detecting the presence of a variant protein in a test sample. Anexemplary kit can comprise antibodies such as a labeled or labelableantibody and a compound or agent for detecting variant proteins in abiological sample; means for determining the amount, or presence/absenceof variant protein in the sample; means for comparing the amount ofvariant protein in the sample with a standard; and instructions for use.

Vectors and Host Cells

The present invention also provides vectors containing theSNP-containing nucleic acid molecules described herein. The term“vector” refers to a vehicle, preferably a nucleic acid molecule, whichcan transport a SNP-containing nucleic acid molecule. When the vector isa nucleic acid molecule, the SNP-containing nucleic acid molecule can becovalently linked to the vector nucleic acid. Such vectors include, butare not limited to, a plasmid, single or double stranded phage, a singleor double stranded RNA or DNA viral vector, or artificial chromosome,such as a BAC, PAC, YAC, or MAC.

A vector can be maintained in a host cell as an extrachromosomal elementwhere it replicates and produces additional copies of the SNP-containingnucleic acid molecules. Alternatively, the vector may integrate into thehost cell genome and produce additional copies of the SNP-containingnucleic acid molecules when the host cell replicates.

The invention provides vectors for the maintenance (cloning vectors) orvectors for expression (expression vectors) of the SNP-containingnucleic acid molecules. The vectors can function in prokaryotic oreukaryotic cells or in both (shuttle vectors).

Expression vectors typically contain cis-acting regulatory regions thatare operably linked in the vector to the SNP-containing nucleic acidmolecules such that transcription of the SNP-containing nucleic acidmolecules is allowed in a host cell. The SNP-containing nucleic acidmolecules can also be introduced into the host cell with a separatenucleic acid molecule capable of affecting transcription. Thus, thesecond nucleic acid molecule may provide a trans-acting factorinteracting with the cis-regulatory control region to allowtranscription of the SNP-containing nucleic acid molecules from thevector. Alternatively, a trans-acting factor may be supplied by the hostcell. Finally, a trans-acting factor can be produced from the vectoritself. It is understood, however, that in some embodiments,transcription and/or translation of the nucleic acid molecules can occurin a cell-free system.

The regulatory sequences to which the SNP-containing nucleic acidmolecules described herein can be operably linked include promoters fordirecting mRNA transcription. These include, but are not limited to, theleft promoter from bacteriophage X, the lac, TRP, and TAC promoters fromE. coli, the early and late promoters from SV40, the CMV immediate earlypromoter, the adenovirus early and late promoters, and retroviruslong-terminal repeats.

In addition to control regions that promote transcription, expressionvectors may also include regions that modulate transcription, such asrepressor binding sites and enhancers. Examples include the SV40enhancer, the cytomegalovirus immediate early enhancer, polyomaenhancer, adenovirus enhancers, and retrovirus LTR enhancers.

In addition to containing sites for transcription initiation andcontrol, expression vectors can also contain sequences necessary fortranscription termination and, in the transcribed region, aribosome-binding site for translation. Other regulatory control elementsfor expression include initiation and termination codons as well aspolyadenylation signals. A person of ordinary skill in the art would beaware of the numerous regulatory sequences that are useful in expressionvectors (see, e.g., Sambrook and Russell, 2000, Molecular Cloning: ALaboratory Manual, Cold Spring Harbor Laboratory Press, Cold SpringHarbor, N.Y.).

A variety of expression vectors can be used to express a SNP-containingnucleic acid molecule. Such vectors include chromosomal, episomal, andvirus-derived vectors, for example, vectors derived from bacterialplasmids, from bacteriophage, from yeast episomes, from yeastchromosomal elements, including yeast artificial chromosomes, fromviruses such as baculoviruses, papovaviruses such as SV40, Vacciniaviruses, adenoviruses, poxviruses, pseudorabies viruses, andretroviruses. Vectors can also be derived from combinations of thesesources such as those derived from plasmid and bacteriophage geneticelements, e.g., cosmids and phagemids. Appropriate cloning andexpression vectors for prokaryotic and eukaryotic hosts are described inSambrook and Russell, 2000, Molecular Cloning: A Laboratory Manual, ColdSpring Harbor Laboratory Press, Cold Spring Harbor, N.Y.

The regulatory sequence in a vector may provide constitutive expressionin one or more host cells (e.g., tissue specific expression) or mayprovide for inducible expression in one or more cell types such as bytemperature, nutrient additive, or exogenous factor, e.g., a hormone orother ligand. A variety of vectors that provide constitutive orinducible expression of a nucleic acid sequence in prokaryotic andeukaryotic host cells are well known to those of ordinary skill in theart.

A SNP-containing nucleic acid molecule can be inserted into the vectorby methodology well-known in the art. Generally, the SNP-containingnucleic acid molecule that will ultimately be expressed is joined to anexpression vector by cleaving the SNP-containing nucleic acid moleculeand the expression vector with one or more restriction enzymes and thenligating the fragments together. Procedures for restriction enzymedigestion and ligation are well known to those of ordinary skill in theart.

The vector containing the appropriate nucleic acid molecule can beintroduced into an appropriate host cell for propagation or expressionusing well-known techniques. Bacterial host cells include, but are notlimited to, E. coli, Streptomyces, and Salmonella typhimurium.Eukaryotic host cells include, but are not limited to, yeast, insectcells such as Drosophila, animal cells such as COS and CHO cells, andplant cells.

As described herein, it may be desirable to express the variant peptideas a fusion protein. Accordingly, the invention provides fusion vectorsthat allow for the production of the variant peptides. Fusion vectorscan, for example, increase the expression of a recombinant protein,increase the solubility of the recombinant protein, and aid in thepurification of the protein by acting, for example, as a ligand foraffinity purification. A proteolytic cleavage site may be introduced atthe junction of the fusion moiety so that the desired variant peptidecan ultimately be separated from the fusion moiety. Proteolytic enzymessuitable for such use include, but are not limited to, factor Xa,thrombin, and enterokinase. Typical fusion expression vectors includepGEX (Smith et al., Gene 67:31-40 (1988)), pMAL (New England Biolabs,Beverly, Mass.) and pRIT5 (Pharmacia, Piscataway, N.J.) which fuseglutathione S-transferase (GST), maltose E binding protein, or proteinA, respectively, to the target recombinant protein. Examples of suitableinducible non-fusion E. coli expression vectors include pTrc (Amann etal., Gene 69:301-415 (1988)) and pET 11d (Studier et al., GeneExpression Technology: Methods in Enzymology 185:60-89 (1990)).

Recombinant protein expression can be maximized in a bacterial host byproviding a genetic background wherein the host cell has an impairedcapacity to proteolytically cleave the recombinant protein (Gottesman,S., Gene Expression Technology: Methods in Enzymology 185, AcademicPress, San Diego, Calif. (1990) 119-128). Alternatively, the sequence ofthe SNP-containing nucleic acid molecule of interest can be altered toprovide preferential codon usage for a specific host cell, for example,E. coli (Wada et al., Nucleic Acids Res. 20:2111-2118 (1992)).

The SNP-containing nucleic acid molecules can also be expressed byexpression vectors that are operative in yeast. Examples of vectors forexpression in yeast (e.g., S. cerevisiae) include pYepSec1 (Baldari, etal., EMBO J. 6:229-234 (1987)), pMFa (Kurjan et al., Cell30:933-943(1982)), pJRY88 (Schultz et al., Gene 54:113-123 (1987)), andpYES2 (Invitrogen Corporation, San Diego, Calif.).

The SNP-containing nucleic acid molecules can also be expressed ininsect cells using, for example, baculovirus expression vectors.Baculovirus vectors available for expression of proteins in culturedinsect cells (e.g., Sf 9 cells) include the pAc series (Smith et al.,Mol. Cell Biol. 3:2156-2165 (1983)) and the pVL series (Lucklow et al.,Virology 170:31-49 (1989)).

In certain embodiments of the invention, the SNP-containing nucleic acidmolecules described herein are expressed in mammalian cells usingmammalian expression vectors. Examples of mammalian expression vectorsinclude pCDM8 (Seed, B. Nature 329:840(1987)) and pMT2PC (Kaufman etal., EMBO J. 6:187-195 (1987)).

The invention also encompasses vectors in which the SNP-containingnucleic acid molecules described herein are cloned into the vector inreverse orientation, but operably linked to a regulatory sequence thatpermits transcription of antisense RNA. Thus, an antisense transcriptcan be produced to the SNP-containing nucleic acid sequences describedherein, including both coding and non-coding regions. Expression of thisantisense RNA is subject to each of the parameters described above inrelation to expression of the sense RNA (regulatory sequences,constitutive or inducible expression, tissue-specific expression).

The invention also relates to recombinant host cells containing thevectors described herein. Host cells therefore include, for example,prokaryotic cells, lower eukaryotic cells such as yeast, othereukaryotic cells such as insect cells, and higher eukaryotic cells suchas mammalian cells.

The recombinant host cells can be prepared by introducing the vectorconstructs described herein into the cells by techniques readilyavailable to persons of ordinary skill in the art. These include, butare not limited to, calcium phosphate transfection,DEAE-dextran-mediated transfection, cationic lipid-mediatedtransfection, electroporation, transduction, infection, lipofection, andother techniques such as those described in Sambrook and Russell, 2000,Molecular Cloning: A Laboratory Manual, Cold Spring Harbor Laboratory,Cold Spring Harbor Laboratory Press, Cold Spring Harbor, N.Y.).

Host cells can contain more than one vector. Thus, differentSNP-containing nucleotide sequences can be introduced in differentvectors into the same cell. Similarly, the SNP-containing nucleic acidmolecules can be introduced either alone or with other nucleic acidmolecules that are not related to the SNP-containing nucleic acidmolecules, such as those providing trans-acting factors for expressionvectors. When more than one vector is introduced into a cell, thevectors can be introduced independently, co-introduced, or joined to thenucleic acid molecule vector.

In the case of bacteriophage and viral vectors, these can be introducedinto cells as packaged or encapsulated virus by standard procedures forinfection and transduction. Viral vectors can be replication-competentor replication-defective. In the case in which viral replication isdefective, replication can occur in host cells that provide functionsthat complement the defects.

Vectors generally include selectable markers that enable the selectionof the subpopulation of cells that contain the recombinant vectorconstructs. The marker can be inserted in the same vector that containsthe SNP-containing nucleic acid molecules described herein or may be ina separate vector. Markers include, for example, tetracycline orampicillin-resistance genes for prokaryotic host cells, anddihydrofolate reductase or neomycin resistance genes for eukaryotic hostcells. However, any marker that provides selection for a phenotypictrait can be effective.

While the mature variant proteins can be produced in bacteria, yeast,mammalian cells, and other cells under the control of the appropriateregulatory sequences, cell-free transcription and translation systemscan also be used to produce these variant proteins using RNA derivedfrom the DNA constructs described herein.

Where secretion of the variant protein is desired, which is difficult toachieve with multi-transmembrane domain containing proteins such asG-protein-coupled receptors (GPCRs), appropriate secretion signals canbe incorporated into the vector. The signal sequence can be endogenousto the peptides or heterologous to these peptides.

Where the variant protein is not secreted into the medium, the proteincan be isolated from the host cell by standard disruption procedures,including freeze/thaw, sonication, mechanical disruption, use of lysingagents, and the like. The variant protein can then be recovered andpurified by well-known purification methods including, for example,ammonium sulfate precipitation, acid extraction, anion or cationicexchange chromatography, phosphocellulose chromatography,hydrophobic-interaction chromatography, affinity chromatography,hydroxylapatite chromatography, lectin chromatography, or highperformance liquid chromatography.

It is also understood that, depending upon the host cell in whichrecombinant production of the variant proteins described herein occurs,they can have various glycosylation patterns, or may benon-glycosylated, as when produced in bacteria. In addition, the variantproteins may include an initial modified methionine in some cases as aresult of a host-mediated process.

For further information regarding vectors and host cells, see CurrentProtocols in Molecular Biology, John Wiley & Sons, N.Y.

Uses of Vectors and Host Cells, and Transgenic Animals

Recombinant host cells that express the variant proteins describedherein have a variety of uses. For example, the cells are useful forproducing a variant protein that can be further purified into apreparation of desired amounts of the variant protein or fragmentsthereof. Thus, host cells containing expression vectors are useful forvariant protein production.

Host cells are also useful for conducting cell-based assays involvingthe variant protein or variant protein fragments, such as thosedescribed above as well as other formats known in the art. Thus, arecombinant host cell expressing a variant protein is useful forassaying compounds that stimulate or inhibit variant protein function.Such an ability of a compound to modulate variant protein function maynot be apparent from assays of the compound on the native/wild-typeprotein, or from cell-free assays of the compound. Recombinant hostcells are also useful for assaying functional alterations in the variantproteins as compared with a known function.

Genetically-engineered host cells can be further used to producenon-human transgenic animals. A transgenic animal is preferably anon-human mammal, for example, a rodent, such as a rat or mouse, inwhich one or more of the cells of the animal include a transgene. Atransgene is exogenous DNA containing a SNP of the present inventionwhich is integrated into the genome of a cell from which a transgenicanimal develops and which remains in the genome of the mature animal inone or more of its cell types or tissues. Such animals are useful forstudying the function of a variant protein in vivo, and identifying andevaluating modulators of variant protein activity. Other examples oftransgenic animals include, but are not limited to, non-human primates,sheep, dogs, cows, goats, chickens, and amphibians. Transgenic non-humanmammals such as cows and goats can be used to produce variant proteinswhich can be secreted in the animal's milk and then recovered.

A transgenic animal can be produced by introducing a SNP-containingnucleic acid molecule into the male pronuclei of a fertilized oocyte,e.g., by microinjection or retroviral infection, and allowing the oocyteto develop in a pseudopregnant female foster animal. Any nucleic acidmolecules that contain one or more SNPs of the present invention canpotentially be introduced as a transgene into the genome of a non-humananimal.

Any of the regulatory or other sequences useful in expression vectorscan form part of the transgenic sequence. This includes intronicsequences and polyadenylation signals, if not already included. Atissue-specific regulatory sequence(s) can be operably linked to thetransgene to direct expression of the variant protein in particularcells or tissues.

Methods for generating transgenic animals via embryo manipulation andmicroinjection, particularly animals such as mice, have becomeconventional in the art and are described in, for example, U.S. Pat.Nos. 4,736,866 and 4,870,009, both by Leder et al., U.S. Pat. No.4,873,191 by Wagner et al., and in Hogan, B., Manipulating the MouseEmbryo, (Cold Spring Harbor Laboratory Press, Cold Spring Harbor, N.Y.,1986). Similar methods are used for production of other transgenicanimals. A transgenic founder animal can be identified based upon thepresence of the transgene in its genome and/or expression of transgenicmRNA in tissues or cells of the animals. A transgenic founder animal canthen be used to breed additional animals carrying the transgene.Moreover, transgenic animals carrying a transgene can further be bred toother transgenic animals carrying other transgenes. A transgenic animalalso includes a non-human animal in which the entire animal or tissuesin the animal have been produced using the homologously recombinant hostcells described herein.

In another embodiment, transgenic non-human animals can be producedwhich contain selected systems that allow for regulated expression ofthe transgene. One example of such a system is the cre/loxP recombinasesystem of bacteriophage P1 (Lakso et al. PNAS 89:6232-6236 (1992)).Another example of a recombinase system is the FLP recombinase system ofS. cerevisiae (O'Gorman et al. Science 251:1351-1355 (1991)). If acre/loxP recombinase system is used to regulate expression of thetransgene, animals containing transgenes encoding both the Crerecombinase and a selected protein are generally needed. Such animalscan be provided through the construction of “double” transgenic animals,e.g., by mating two transgenic animals, one containing a transgeneencoding a selected variant protein and the other containing a transgeneencoding a recombinase.

Clones of the non-human transgenic animals described herein can also beproduced according to the methods described in, for example, Wilmut, I.et al. Nature 385:810-813 (1997) and PCT International Publication Nos.WO 97/07668 and WO 97/07669. In brief, a cell (e.g., a somatic cell)from the transgenic animal can be isolated and induced to exit thegrowth cycle and enter G_(o) phase. The quiescent cell can then befused, e.g., through the use of electrical pulses, to an enucleatedoocyte from an animal of the same species from which the quiescent cellis isolated. The reconstructed oocyte is then cultured such that itdevelops to morula or blastocyst and then transferred to pseudopregnantfemale foster animal. The offspring born of this female foster animalwill be a clone of the animal from which the cell (e.g., a somatic cell)is isolated.

Transgenic animals containing recombinant cells that express the variantproteins described herein are useful for conducting the assays describedherein in an in vivo context. Accordingly, the various physiologicalfactors that are present in vivo and that could influence ligand orsubstrate binding, variant protein activation, signal transduction, orother processes or interactions, may not be evident from in vitrocell-free or cell-based assays. Thus, non-human transgenic animals ofthe present invention may be used to assay in vivo variant proteinfunction as well as the activities of a therapeutic agent or compoundthat modulates variant protein function/activity or expression. Suchanimals are also suitable for assessing the effects of null mutations(i.e., mutations that substantially or completely eliminate one or morevariant protein functions).

For further information regarding transgenic animals, see Houdebine,“Antibody manufacture in transgenic animals and comparisons with othersystems”, Curr Opin Biotechnol. 2002 December; 13(6):625-9; Petters etal., “Transgenic animals as models for human disease”, Transgenic Res.2000; 9(4-5):347-51; discussion 345-6; Wolf et al., “Use of transgenicanimals in understanding molecular mechanisms of toxicity”, J PharmPharmacol. 1998 June; 50(6):567-74; Echelard, “Recombinant proteinproduction in transgenic animals”, Curr Opin Biotechnol. 1996 October;7(5):536-40; Houdebine, “Transgenic animal bioreactors”, Transgenic Res.2000; 9(4-5):305-20; Pirity et al., “Embryonic stem cells, creatingtransgenic animals”, Methods Cell Biol. 1998; 57:279-93; and Robl etal., “Artificial chromosome vectors and expression of complex proteinsin transgenic animals”, Theriogenology. 2003 Jan. 1; 59 (1):107-13.

EXAMPLES

The following examples are offered to illustrate, but not to limit, theclaimed invention.

Example One: Statistical Analysis of SNPs Associated with Psoriasis

Overview

A multi-tiered genetic association study of 25,215 SNPs in threecase-control sample sets (1,446 patients and 1,432 controls) identifiedthree IL13-linked SNPs (rs1800925, rs20541, rs848) associated withpsoriasis. These SNPs had psoriasis susceptibility effects (jointallelic ORs: 0.76→0.78; P_(comb): 1.3E-032.50E-04), and the associationpatterns were consistent across the sample sets, with the minor allelesbeing protective. Haplotype analyses identified one common, susceptiblehaplotype CCG (joint allelic OR=1.27; P_(comb)=1.88E-04) and a lesscommon, protective haplotype TTT (joint allelic OR=0.74;P_(comb)=7.05E-04). In combination with the other known genetic riskfactors, HLA-C, IL12B and IL23R, the variants reported here generate an11-fold psoriasis-risk differential. Residing in the 5q31 cytokine genecluster, IL13 encodes an important T-cell derived cytokine thatregulates cell-mediated immunity.

Results and Discussion

Three SNPs within 4 kb of one another in the IL13-region in 5q31 met oursignificance criteria in the pooled-genotyping phase of our study:rs1800925 (located 1 kb 5′ of the IL13 coding region), rs20541 (an IL13exon 4 missense SNP, Q144R), and rs848 (located within the 3′ UTR regionof IL13).

Individual genotyping of these three markers in all three sample setsshowed each of the markers was consistent with Hardy-Weinbergequilibrium in both cases and controls of each sample set (Table 5).Minor allele frequencies for all three SNPs were nearly the same:approximately 18-20% in controls and decreasing to 14-17% in cases. Forall three SNPs, combining P-values across the three sample sets usingFisher's combined probability method generated significant values forboth allelic and genotypic tests (allelic: P_(rs1800925)=2.50E-04,P_(rs20541)=0.0013, P_(rs848)=0.0017; genotypic P_(rs1800925)=0.0029,P_(rs20541)=0.0022, P_(rs848)=0.0027). Notably, the 5′ SNP, rs1800925,and the 3′ UTR SNP, rs848, were significant (P_(allelic)<0.05) in allthree sample sets.

Pairwise LD values between these three associated SNPs were calculated,using the r² measure applied to all individuals in sample set 1. Two ofthe SNPs, rs20541 and rs848, were in very high LD (r²=0.98). Theremaining SNP, rs1800925 was not as highly correlated with the other twoSNPs (r²=0.24 for both comparisons).

Haplotype analyses can often reveal important cis-acting effects amongalleles at closely-linked sites. We used the program Haplo.Stats (SchaidD J, Rowland C M, Tines D E, Jacobson R M, Poland G A. Score tests forassociation between traits and haplotypes when linkage phase isambiguous. Am J Hum Genet 2002; 70: 425-434) to estimate haplotypes forthese three SNPs and to perform a test of psoriasis association. Thisprogram calculates P-values for each haplotype and also a globalP-value. Results for the three SNPs (rs1800925, rs20541 and rs848)showed four common haplotypes in each sample set (as expected from theLD patterns), but only the CCG haplotype (carrying the major allele ateach site) was significant in all three studies (SS1 P=0.0288, SS2P=0.0177, and SS3 P=0.0037) (Table 6). A combined analysis showedassociation for this haplotype (P_(comb)=1.84E-04) and also revealed asecond associated haplotype, TTT (P_(comb)=7.05E-04) which carries theminor allele at each site and exhibited protective effects. Overall, thesusceptible haplotype, CCG, had a frequency of 72.1% in controlsincreasing to 76.5% in cases while the protective haplotype, TTT, had afrequency of 11.5% in controls decreasing to 8.8% in cases. The risk CCGhaplotype had a joint OR=1.27 and the protective haplotype had a jointOR=0.74.

IL-13 is an immuno-regulatory cytokine produced primarily by activatedTh2 cells that exerts its effect by binding to its receptor andactivating the STAT6-mediated signal transduction pathway. IL-13 hasbeen most prominently implicated as a critical mediator of an allergicinflammatory response, and genetic variants of IL13 are known to beassociated with susceptibility to asthma in humans (Heinzmann A, Mao XQ, Akaiwa M, Kreomer R T, Gao P S, Ohshima K et al. Genetic variants ofIL-13 signalling and human asthma and atopy. Hum Mol Genet 2000; 9:549-559). Genetic variation in IL13 has also been associated with therisk of atopic dermatitis in a Japanese study (Tsunemi Y, Saeki H,Nakamura K, Sekiya T, Hirai K, Kakinuma T et al. Interleukin-13 genepolymorphism G4257A is associated with atopic dermatitis in Japanesepatients. J Dermatol Sci 2002; 30: 100-107) and although there has beenno prior report for a role of IL-13 in psoriasis, altered expression ofthe two IL-13 receptor chains, IL4-Rα and IL-13α1, has been observed inthe skin of psoriasis patients (Cancino-Diaz J C, Reyes-Maldonado E,Banuelos-Panuco C A, Jimenez-Zamudio L, Garcia-Latorre E, Leon-DorantesG et al. Interleukin-13 receptor in psoriatic keratinocytes:overexpression of the mRNA and underexpression of the protein. J InvestDermatol 2002; 119: 1114-1120). Thus IL13 represents a reasonablebiological candidate gene for the development of psoriasis.

However, as the initial single marker results were derived from a screenof a large number of SNPs, false positive results due to selection biasfrom multiple testing must be considered. Given the extremely limitednumber of loci tested in the third sample set (N=three loci—IL12B, IL23Rand IL13), our results argue against a false positive error. Using theDunn-Sidak method of calculating an experimentwise P-value (Sokal R R,Rohlf F J. Biometry 3^(rd) ed. W.H. Freeman and Company, New York, 1995)for the third sample set, analysis of data at the 5′ marker, rs1800925,shows it retains statistical significance after adjusting for multipletesting (P_(adj)=0.0199). In addition, although simulation results (notshown) indicate that these results could have been generated by a trulyassociated marker, there is still a reasonable chance that the observedresults arose from a null model. Finally, previous analyses ofpopulation stratification in these sample sets suggested that theconfounding impact on the genetic association results was marginal(Cargill M, Schrodi S J, Chang M, Garcia V E, Brandon R, Callis K P etal. A large-scale genetic association study confirms IL12B and leads tothe identification of IL23R as psoriasis-risk genes. Am J Hum Genet2007; 80:273-290). Three other gene regions with substantial andreplicated association evidence—HLA-C, IL12B, and IL23R—have been shownto affect the risk of psoriasis. Given the modest effect sizes of theseand other gene variants associated with common diseases, multi-locusestimates of differential risk are informative measures (Janssens A C,Moonesinghe R, Yang Q, Steyerberg E W, van Duijn C M, Khoury M J. Theimpact of genotype frequencies on the clinical validity of genomicprofiling for predicting common chronic diseases. Genet Med 2007; 9:528-535). In an effort to better elucidate the strength of thepsoriasis-predisposing effects from all four loci, we estimated theprobability of psoriasis given genotypes at HLA-C and thecytokine-pathway genes IL12B, IL23R and IL13. Conditional independencebetween loci was assumed (three independent methods substantiated thisassumption, see the Brief Description of the Figure section) and weemployed Bayes' theorem for the calculation. Assuming apsoriasis-prevalence of 3%, these calculations show that thedifferential risk between the Very High and Low risk multi-locusgenotype groups is over 11-fold (FIG. 1 ; Table 7). Greater than 10% ofthe general North American white population carry gene combinationswhich increase their risk of psoriasis to over 0.08; whereas 33% of theNorth American white population are at less than half the risk ofdisease compared to the general population.

The 5q31 region harboring IL13 has been identified as a susceptibilitylocus for psoriasis in a previous family-based linkage study ofpsoriasis (Friberg C, Bjorck K, Nilsson S, Inerot A, Wahlstrom J,Samuelsson, L. Analysis of chromosome 5q31-42 and psoriasis:confirmation of a susceptibility locus but no association with SNPswithin SLC22A4 and SLC22A5. J Invest Dermatol 2006; 126: 998-1002), aswell as for other inflammatory conditions including Crohn's disease(Rioux J D, Silverberg M S, Daly M J, Steinhart A H, McLeod R S,Griffiths A M et al. Genomewide search in Canadian families withinflammatory bowel disease reveals two novel susceptibility loci. Am JHum Genet 2000; 66: 1863-1870; Rioux J D, Daly M J, Silverberg M S,Lindblad K, Steinhart H, Cohen Z et al. Genetic variation in the 5q31cytokine gene cluster confers susceptibility to Crohn disease. Nat Genet2001; 29: 223-228; Mirza M M, Fisher S A, King K, Cuthbert A P, Hampe J,Sanderson J et al. Genetic evidence for interaction of the 5q31 cytokinelocus and the CARD15 gene in Crohn disease. Am J Hum Genet 2003; 72:1018-1022; Wellcome Trust Case Control Consortium. Genome-wideassociation study of 14,000 cases of seven common diseases and 3,000shared controls. Nature 2007; 447: 661-678) and bronchialhyperresponsiveness/atopy/asthma phenotypes (Heinzmann A, Mao X Q,Akaiwa M, Kreomer R T, Gao P S, Ohshima K et al. Genetic variants ofIL-13 signalling and human asthma and atopy. Hum Mol Genet 2000; 9:549-559; Postma D S, Bleecker E R, Amelung P J, Holroyd K J, Xu J,Panhuysen C I M et al. Genetic susceptibility to asthma: bronchialhyperresponsiveness coinherited with a major gene for atopy. New Eng JMed 1995; 333: 894-900; Howard T D, Whittaker P A, Zaiman A L, KoppelmanG H, Xu J, Hanley M T et al. Identification and association ofpolymorphisms in the interleukin-13 gene with asthma and atopy in aDutch population. Am J Respir Cell Mol Biol 2001; 25: 377-384). The linkbetween psoriasis and Crohn's disease appears to be particularly strong,as evidenced by (i) a similar aberrant response in T-helper cells(Neimann A L, Porter S B, Gelfand J M. The epidemiology of psoriasis.Expert Rev Dermatol 2006; 1: 63-75), (ii) familial clustering of the twodiseases (Neimann A L, Porter S B, Gelfand J M. The epidemiology ofpsoriasis. Expert Rev Dermatol 2006; 1: 63-75), and (iii) theobservation that the same allele in the IL23R SNP, rs11209026, isassociated with risk for both diseases (Cargill M, Schrodi S J, Chang M,Garcia V E, Brandon R, Callis K P et al. A large-scale geneticassociation study confirms IL12B and leads to the identification ofIL23R as psoriasis-risk genes. Am J Hum Genet 2007; 80:273-290; Duerr RH, Taylor K D, Brant S R, Rioux J D, Silverberg M S, Daly M J et al. Agenome-wide association study identifies IL23R as an inflammatory boweldisease gene. Science 2006; 314: 1461-1463). Genes contributing toasthma and psoriasis risk, such as ADAM33, also appear to overlap(Lesueur F, Oudot T, Heath S, Foglio M, Lathrop M, Prud'homme J F et al.ADAM33, a new candidate for psoriasis susceptibility. PLoS ONE 2007;2:e906).

In conclusion, we have presented results of three IL13 SNPs associatedwith psoriasis. A common susceptibility haplotype, CCG, carried by 92%of controls produced a consistent effect (joint OR=1.27) that achievedstatistical significance (P_(comb)=1.88E-04). Conversely, aless-frequent haplotype, TTT, generates protective effects in our study(joint OR=0.74) with fairly similar significance (P_(comb)=7.05E-04).Further, combining the genotypic effects at the SNP directly 5′ of IL13(rs1800925) with previously-reported susceptibility variants at HLA-C,IL12B and IL23R demonstrates a range of psoriasis relative risk from0.34, increasing 11-fold to 3.83.

Example Two: Statistical Analysis of Additional SNPs Associated withPsoriasis

As disclosed above in Example One, we described that three SNPs(rs1800925, rs20541 and rs848) in the IL13-region at the 3′ end of the5q31 cytokine gene cluster were associated with psoriasis in a large,multi-tiered, genetic association study (Chang, M., Li, Y., Yan, C.,Callis-Duffin, K. P., Matsunami, N., Garcia, V. E., Cargill, M.,Civello, D., Bui, N., Catanese, J. J., Leppert, M. F. et al. (2008)Variants in the 5q31 cytokine gene cluster are associated withpsoriasis. Genes Immun, doi:10.1038/sj.gene.6364451). The 5q31 genomicregion contains a cluster of cytokine and immune-related genes,including interleukin (IL) genes IL3, IL4, IL5, and IL13, interferonregulatory factor-1 (IRF-1), colony-stimulating factor-2 (CSF2) andT-cell transcription factor-7 (TCF7), all excellent biological candidategenes. This region shows extended marker-marker correlation; forexample, examination of the CEU HapMap dataset reveals that a number ofmarkers within the 100 kb interval immediately upstream of IL13 are inrelatively strong LD (r²>0.5) with one of the significant IL13 SNPs,rs20541. Numerous other markers extending as far as 1 Mb upstream ofIL13 also show moderate LD with rs20541 (r²>0.2). Therefore, to moreprecisely define the causal variants in the 5q31 region, we carried outa comprehensive analysis of the genetic variation in this region usingthree large, independent sample sets, totaling 1,448 cases and 1,385controls, and report findings from association tests of the markers withpsoriasis risk.

Results

Single Marker Association Test Identifies Multiple SNPs Associated withPsoriasis

Examination of the 5q31 LD structure in the CEU HapMap Phase II dataset,led us to focus our fine-mapping to a 725 kb region that delimits theentire cytokine cluster, extending from ˜50 kb upstream of IL3 to ˜50 kbdownstream of IL4 (FIG. 2A). This region was targeted with 90finemapping SNPs, primarily selected as tagging markers (see Materialsand Methods). Allelic association tests of the 90 SNPs with psoriasisidentified nine significant ones (P<0.05, FIG. 2A and Table 12) in a 370kb region extending from SLC22A4 to KIF3A and including IRF1, IL5, IL13and IL4; these nine SNPs were then genotyped in two other case controlsample sets. Although the significance of these nine markers varied inthe two follow-up sample sets (FIG. 2A and Table 13), all nine weresignificant in a combined analysis of the three sample sets(Mantel-Haenszel P_(combined)<0.05, Table 8 & Table 13). Breslow-Daytests provided no evidence for heterogeneity of effect across samplesets except for one marker, rs11568506 (odds ratio (OR) homogeneity:P_(rs11568506)=0.032; P>0.05 for all other markers). Based on theP_(comb)-values, none of the nine markers were more significant thanrs1800925 (Mantel-Haenszel P_(combined)=0.00015), one of the three IL13markers in our original report (Chang, M., Li, Y., Yan, C.,Callis-Duffin, K. P., Matsunami, N., Garcia, V. E., Cargill, M.,Civello, D., Bui, N., Catanese, J. J., Leppert, M. F. et al. (2008)Variants in the 5q31 cytokine gene cluster are associated withpsoriasis. Genes Immun, doi:10.1038/sj.gene.6364451), although some werecomparable (e.g. P=0.00022 for the IL4 marker rs2227282). Odds ratiosconferred by these variants were all modest (Table 8 & Table 13).

Conditional Analysis Reveals Two Independent SNPs

To tease apart association signals from patterns of LD and determinewhich of these nine SNPs were independently associated with psoriasisrisk, we performed pairwise tests of association for each SNP, using thecombined datasets, conditioning on the genotypes at the other SNPs andevaluated the significance of these results using a permutation test(10,000 permutations) (Table 9). This approach is similar to thehaplotype method (Valdes, A. M. and Thomson, G. (1997) Detectingdisease-predisposing variants: the haplotype method. Am J Hum Genet, 60,703-716) and has been previously described (Cargill, M., Schrodi, S. J.,Chang, M., Garcia, V. E., Brandon, R., Callis, K. P., Matsunami, N.,Ardlie, K. G., Civello, D., Catanese, J. J. et al. (2007) A large-scalegenetic association study confirms IL12B and leads to the identificationof IL23R as psoriasis-risk genes. Am J Hum Genet, 80, 273-390). Notsurprisingly, the significant association of various SNPs with psoriasisdisappeared upon conditioning on other markers. Most notably, thesignificance of all other markers except rs11568506 (in SLC22A4;P=0.0105) was abolished upon conditioning on rs1800925. Conversely,association of rs1800925 remained strong (P=0.0002) upon conditioning onrs11568506. Together these observations suggest that rs11568506 andrs1800925 make independent contributions to psoriasis risk. The genotypecorrelation between rs11568506 and rs1800925 is very low (r²=0.006),while that between rs1800925 and the other 10 SNPs varied from 0.016 to0.801 (Table 14).

Next we assessed whether SNPs in high LD with rs1800925 could be moresignificantly associated with disease. Genotype data were retrieved fromthe HapMap CEU dataset (release #22, phase II April 07), covering 1 Mbon each side of the IL13 gene, and the correlation (as determined by r²values) between rs1800925 and all other 1559 SNPs was calculated. Atotal of 32 markers were highly correlated with rs1800925 (r²>0.8)(Table 15), 30 of which were in absolute LD (r²=1) with one another. Oneof these 30 markers, rs2897443 (r² with rs1800925=0.897), which wasgenotyped in all three psoriasis sample sets (Table 13), was nearly10-fold less significant than rs1800925 (P_(rs2897443)=0.001 vsP_(rs1800925)=0.00015). In addition, rs2897443 was no longer significantafter conditioning on rs1800925 (P=0.2168) while, rs1800925 remainedsignificant after conditioning on rs2897443 (P=0.042). The other twomarkers (rs2706370 and rs12187537) were not genotyped; however, theywere highly correlated with rs2897443 (r²=0.94) and less so withrs1800925 (r²=0.829 and 0.817, respectively) making it unlikely thatthey were more significantly associated with disease than rs1800925.

Given that two markers, rs11568506 and rs1800925, show independentassociation with psoriasis, we carried out haplotype analyses using bothmarkers in each of the three individual sample sets and in a combinedanalysis of all three sample sets. Although it's difficult to determinewhether the two independent markers reside in the same LD block (FIG.2B), the number of double heterozygotes was small (7 cases and 16controls out of 2,800 samples; see Table 16); therefore phase could beunambiguously established in 99.2% of all individuals. Three haplotypeswere observed, with the fourth being relatively rare (<0.001 in cases orcontrols) due to the low frequency of rs11568506. The two commonhaplotypes were significantly associated with psoriasis in two of thethree sample sets; they were not significant in sample set 2 althoughthe odds ratios were in the same direction as in the other two samplesets (Table 10). In a meta-analysis, both common haplotypes weresignificantly associated with psoriasis, and significance of the mostcommon haplotype, GC, was markedly higher than any single SNP(P=5.67×10⁻⁶ for the haplotype vs. 1.5×10⁻⁴ for rs1800925). The observedeffect sizes in the combined analysis of all sample sets were 1.37 forthe predisposing haplotype GC (rs11568506-rs1800925) (frequency: 0.827in cases vs 0.777 in controls) and 0.75 for the protective haplotype GT(frequency: 0.156 in cases vs 0.198 in controls).

Distinct SNPs are Associated with Psoriasis and Crohn's Disease

Previous studies have identified linkage of the 5q31 locus and/orassociation of specific variants in this region with several otherdiseases, including CD and asthma/allergic disorders (Heinzmann, A.,Mao, X. Q., Akaiwa, M., Kreomer, R. T., Gao, P. S., Ohshima, K.,Umeshita, R., Abe, Y., Braun, S., Yamashita, T. et al. (2000) Geneticvariants of IL-13 signalling and human asthma and atopy. Hum Mol Genet,9, 549-559; Howard, T. D., Whittaker, P. A., Zaiman, A. L., Koppelman,G. H., Xu, J., Hanley, M. T., Meyers, D. A., Postma, D. S. and Bleecker,E. R. (2001) Identification and association of polymorphisms in theinterleukin-13 gene with asthma and atopy in a Dutch population. Am JRespir Cell Mol Biol, 25, 377-384; Postma, D. S., Bleecker, E. R.,Amelung, P. J., Holroyd, K. J., Xu, J., Panhuysen, C. I., Meyers, D. A.and Levitt, R. C. (1995) Genetic susceptibility to asthma-bronchialhyperresponsiveness coinherited with a major gene for atopy. N Engl JMed, 333, 894-900). Because psoriasis and CD may share common geneticetiology (psoriasis is approximately five times more common in Crohn'sdisease patients than in controls (Lee, F. I., Bellary, S. V. andFrancis, C. (1990) Increased occurrence of psoriasis in patients withCrohn's disease and their relatives. Am J Gastroenterol, 85, 962-963)and the same missense SNP in IL23R is associated with both diseases(Duerr, R. H., Taylor, K. D., Brant, S. R., Rioux, J. D., Silverberg, M.S., Daly, M. J., Steinhart, A. H., Abraham, C., Regueiro, M., Griffiths,A. et al. (2006) A genome-wide association study identifies IL23R as aninflammatory bowel disease gene. Science, 314, 1461-1463; Cargill, M.,Schrodi, S. J., Chang, M., Garcia, V. E., Brandon, R., Callis, K. P.,Matsunami, N., Ardlie, K. G., Civello, D., Catanese, J. J. et al. (2007)A large-scale genetic association study confirms IL12B and leads to theidentification of IL23R as psoriasis-risk genes. Am J Hum Genet, 80,273-390; Capon, F., Di Meglio, P., Szaub, J., Prescott, N.J., Dunster,C., Baumber, L., Timms, K., Gutin, A., Abkevic, V., Burden, A. D. et al.(2007) Sequence variants in the genes for the interleukin-23 receptor(IL23R) and its ligand (IL12B) confer protection against psoriasis. HumGenet, 122, 201-206; Smith, R. L., Warren, R. B., Eyre, S., Ho, P., Ke,X., Young, H. S., Griffiths, C. E. and Worthington, J. (2007)Polymorphisms in the IL-12beta and IL-23R Genes Are Associated withPsoriasis of Early Onset in a UK Cohort. J Invest Dermatol.doi:10.1038/sj.jid.5701140; Nair, R. P., Ruether, A., Stuart, P. E.,Jenisch, S., Tejasvi, T., Hiremagalore, R., Schreiber, S., Kabelitz, D.,Lim, H. W., Voorhees, J. J. et al. (2008) Polymorphisms of the IL12B andIL23R Genes Are Associated with Psoriasis. J Invest Dermatol.doi:10.1038/sj.jid.5701255), we were also interested in testing ourpsoriasis sample sets for 5q31 SNPs showing strong association with CD.The WTCCC reported several highly significant SNPs in this region intheir CD dataset (Wellcome Trust Case Control Consortium. (2007)Genome-wide association study of 14,000 cases of seven common diseasesand 3,000 shared controls. Nature, 447, 661-678). When selecting our setof 103 tagging SNPs, we specifically selected those SNPs, in groups ofhighly correlated markers, with evidence of association with CD in theWTCCC sample set. Of the 90 fine-mapping markers described above, fivewere identical to those showing strong association with CD (rs2285673,rs4540166, rs2522057, rs6596075 and rs10077785, all with P<5×10⁻⁵ in˜2,000 cases and ˜3,000 controls (Wellcome Trust Case ControlConsortium. (2007) Genome-wide association study of 14,000 cases ofseven common diseases and 3,000 shared controls. Nature, 447, 661-678)and genotyped in all three of our psoriasis sample sets. None weresignificant in sample set 1 (all P>0.05), but one SNP, rs2522057, wassignificantly associated with psoriasis in a meta-analyses of the threesample sets combined (P=0.022) (Table 11). The pairwise conditionalassociation test, however, showed that this significant associationcould be accounted for by the IL13 marker, rs1800925 (P=0.60 forrs2522057 conditioned upon rs1800925, whereas rs1800925 remainedsignificant when conditioned upon rs2522057, P=0.017). Assuming a type Ierror rate of 0.05 and the population allele frequency observed in theWTCCC study, our combined analysis had 90% power to detect an alleliceffect equal to an OR of 1.25, similar to the reported OR of 1.37 forrs6596075, which tags the 5q31 CD risk haplotype (Wellcome Trust CaseControl Consortium. (2007) Genome-wide association study of 14,000 casesof seven common diseases and 3,000 shared controls. Nature, 447,661-678). Thus variants contributing to CD risk in this genomic region,which map 5′ of the psoriasis-associated SNPs near the LOC441108-region,do not make an independent contribution to the etiology of psoriasis inour sample sets. In addition, although neither of the two independentpsoriasis markers, rs1800925 and rs11568506, was tested in the WTCCC'sCD sample set, four other markers in high LD with rs1800925 (r²=0.9 forall) were tested but were not significant in their study. Therefore,association with CD and psoriasis in this region appears to be explainedby different variants.

Discussion

Our analysis of the 5q31 cytokine cluster reveals that multiple SNPs aresignificantly associated with psoriasis risk; however, incorporating LDinto our analysis identified two SNPs independently associated withpsoriasis: rs1800925 in IL13 and rs11568506 in SLC22A4, also known asorganic cation transporter 1 (OCTN1). The observed significance was onlymarginal for the SLC22A4 marker (Mantel-Haenszel P_(combined)=0.043).However, combining the genotype information for this marker with themore frequent IL13 marker, which is also more significant(Mantel-Haenszel P_(combined)=0.00015), resulted in two commonpsoriasis-associated haplotypes that were both highly significant. Inparticular, the major risk haplotype, with a control allele frequency of0.777 increasing to 0.827 in cases, showed more pronounced associationwith psoriasis (P_(combined)=5.67×10⁻⁶, OR=1.37).

The biological interpretation of this observation (i.e., variants in twolinked genes) is not straight-forward; however, both SLC22A4 and IL13are putative genetic risk factors for other autoimmune orautoinflammatory disorders. Specifically, two-locus functionalpolymorphisms (haplotypes) in SLC22A4 and the adjacent SLC22A5 geneshave been reported to be associated with CD (Peltekova, V. D., Wintle,R. F., Rubin, L. A., Amos, C. I., Huang, Q., Gu, X., Newman, B., VanOene, M., Cescon, D., Greenberg, G. et al. (2004) Functional variants ofOCTN cation transporter genes are associated with Crohn disease. NatGenet, 36, 471-475), although definitive causal variants remain to bedetermined (Silverberg, M. S. (2006) OCTNs: will the real IBD5 geneplease stand up? World J Gastroenterol, 12, 3678-3681; Silverberg, M.S., Duerr, R. H., Brant, S. R., Bromfield, G., Datta, L. W., Jani, N.,Kane, S. V., Rotter, J. I., Philip Schumm, L., Hillary Steinhart, A., etal. (2007) Refined genomic localization and ethnic differences observedfor the IBD5 association with Crohn's disease. Eur J Hum Genet, 15,328-335). Variation in IL13, an immunoregulatory cytokine produced byactivated T helper 2-type (Th2) cells, has been most prominentlyassociated with asthma (Heinzmann, A., Mao, X. Q., Akaiwa, M., Kreomer,R. T., Gao, P. S., Ohshima, K., Umeshita, R., Abe, Y., Braun, S.,Yamashita, T. et al. (2000) Genetic variants of IL-13 signalling andhuman asthma and atopy. Hum Mol Genet, 9, 549-559, as well as atopicdermatitis (Tsunemi, Y., Saeki, H., Nakamura, K., Sekiya, T., Hirai, K.,Kakinuma, T., Fujita, H., Asano, N., Tanida, Y., Wakugawa, M. et al.(2002) Interleukin-13 gene polymorphism G4257A is associated with atopicdermatitis in Japanese patients. J Dermatol Sci, 30, 100-107). Thus bothgenes have strong a priori plausibility as risk factors of psoriasis,particularly as multiple autoimmune disorders have been associated withthe same genetic variant (Gregersen, P. K., Lee, H. S., Batliwalla, F.and Begovich, A. B. (2006) PTPN22: setting thresholds for autoimmunity.Semin Immunol, 18, 214-223; Yamada, R. and Ymamoto, K. (2005) Recentfindings on genes associated with inflammatory disease. Mutat Res, 573,136-151). Strong biological evidence for the involvement of SLC22A4 orIL13 in the pathogenesis of psoriasis has, however, not yet beenreported. Further experimentation should help determine whether thesegenes play a role in the disease process.

The two identified SNPs are located in an intron of SLC22A4 and near the5′ end of IL13, respectively, with no predictive functional significancebased on the current SNP annotation, although rs11568506 is 43 bp from aPOU2F1 transcription factor binding site, which exhibits a high degreeof conservation across multiple placental mammals. In the absence of avalidated role in gene regulation for these SNPs, and the presence ofseveral other excellent biological candidate genes within this region aswell as critical regulatory elements (Mohrs, M., Blankespoor, C. M.,Wang, Z., Loots, G. G., Afzal V., Hadeiba, H., Shinkai, K., Rubin, E.M., and Locksley, R. M. (2001) Deletion of a coordinate regulator oftype 2 cytokine expression in mice. Nat Immunol. 2, 842-847), it istempting to speculate that untested, causal genetic variant(s) lie onthe particular haplotype defined by the two independent SNPs identifiedhere. Although our comprehensive, HapMap-based analysis of the variationin this region provided no evidence for such a marker, we were unable todevelop assays for tagging SNPS covering 13.6% of the variation. Inaddition, SNPs not available in the HapMap, such as for the mostsignificant marker, rs1800925, may explain these results. Similarly,other genetic variants (insertions, deletions, etc) which have beenimplicated in the etiology of various complex diseases, includingpsoriasis (see, for example, Hollox, E. J., Huffmeier, U., Zeeuwen, P.L., Palla, R., Lascorz, J., Rodijk-Olthuis, D., van de Kerkhof, P. C.,Traupe, H., de Jongh, G., den Heijer, M. et al. (2008) Psoriasis isassociated with increased beta-defensin genomic copy number. Nat Genet,40, 23-25, and Fanciulli, M., Norsworthy, P. J., Petretto, E., Dong, R.,Harper, L., Kamesh, L., Heward, J. M., Gough, S. C., de Smith, A.,Blakemore, A. I. et al. (2007) FCGR3B copy number variation isassociated with susceptibility to systemic, but not organ-specific,autoimmunity. Nat Genet, 39, 721-723), may be responsible for modulatingdisease susceptibility.

Although the recent identification of IL23R variants associated withpsoriasis and CD solidifies the notion that genetic etiology may overlapbetween these two diseases (Duerr, R. H., Taylor, K. D., Brant, S. R.,Rioux, J. D., Silverberg, M. S., Daly, M. J., Steinhart, A. H., Abraham,C., Regueiro, M., Griffiths, A. et al. (2006) A genome-wide associationstudy identifies IL23R as an inflammatory bowel disease gene. Science,314, 1461-1463; Cargill, M., Schrodi, S. J., Chang, M., Garcia, V. E.,Brandon, R., Callis, K. P., Matsunami, N., Ardlie, K. G., Civello, D.,Catanese, J. J. et al. (2007) A large-scale genetic association studyconfirms IL12B and leads to the identification of IL23R aspsoriasis-risk genes. Am J Hum Genet, 80, 273-390), our data suggestthat this is unlikely to be the case for the 5q31 locus, where linkagesignals have been detected for both diseases (Rioux, J. D., Silverberg,M. S., Daly, M. J., Steinhart, A. H., McLeod, R. S., Griffiths, A. M.,Green, T., Brettin, T. S., Stone, V., Bull, S. B. et al. (2000)Genomewide search in Canadian families with inflammatory bowel diseasereveals two novel susceptibility loci. Am J Hum Genet, 66, 1863-1870;Rioux, J. D., Daly, M. J., Silverberg, M. S., Lindblad, K., Steinhart,H., Cohen, Z., Delmonte, T., Kocher, K., Miller, K., Guschwan, S. et al.(2001) Genetic variation in the 5q31 cytokine gene cluster conferssusceptibility to Crohn disease. Nat Genet, 29, 223-228; Samuelsson, L.,Enlund, F., Torinsson, A., Yhr, M., Inerot, A., Enerback, C., Wahlstrom,J., Swanbeck, G. and Martinsson, T. (1999) A genome-wide search forgenes predisposing to familial psoriasis by using a stratificationapproach. Hum Genet, 105, 523-529). Several previously reportedCD-associated markers in the 5q31 region, including one that tags a riskhaplotype (rs6596075), were not significant in our psoriasis sample setsand rs2522057, which showed modest association the combined analysis,could be explained by LD with the most significant marker, rs1800925.This is despite the fact that our sample sets had sufficient power todetect an effect size similar to that of the same markers observed in CDor the majority of the SNPs recently identified for other complexdiseases (Wellcome Trust Case Control Consortium. (2007) Genome-wideassociation study of 14,000 cases of seven common diseases and 3,000shared controls. Nature, 447, 661-678). This observation is consistentwith a recent report that failed to detect a significant associationbetween psoriasis and three other CD-associated SNPs in SLC22A4 andSLC22A5 (Friberg, C., Bjorck, K., Nilsson, S., Inerot, A., Wahlstrom, J.and Samuelsson, L. (2006) Analysis of chromosome 5q31-32 and psoriasis:confirmation of a susceptibility locus but no association with SNPswithin SLC22A4 and SLC22A5. J Invest Dermatol, 126, 998-1002). It ispossible that the lack of association may be partly confounded by thefact that the actual causal CD variants have not been tested. However,judging from the significance level observed in the WTCCC study(Wellcome Trust Case Control Consortium. (2007) Genome-wide associationstudy of 14,000 cases of seven common diseases and 3,000 sharedcontrols. Nature, 447, 661-678), and unless there are significantdifferences in the LD structure between their sample sets and ours(which is unlikely), we favor the interpretation that susceptibility topsoriasis and CD are affected by distinct genetic variants at this locusor the same variants but with different effect sizes.

Finally, it is possible that we may not have the power to detectconditional association effects in our sample sets. Thus, although thesignificance of all other markers except rs11568506 can be accounted forby rs1800925, we cannot exclude the possibility that these othermarkers, particularly the stronger ones in IL13 and IL4, makeadditional, independent contributions to disease risk. In addition, thepossibility that our current finding is false positive cannot becompletely discounted, since the observed significance will not survivemultiple testing corrections if all markers tested in our previousgenome-wide scan and in this study are considered—which is generallydeemed conservative. However, in an unpublished GWA study of ˜1400Caucasian cases and ˜1400 Caucasian controls, two of our originalIL13-associated SNPs, rs20541 and rs848, exhibit very strong evidencefor association. These data suggest markers in the 5q31 region are truepsoriasis risk markers and suggest that variants in both the IL13 andSLC22A4 regions independently contribute to psoriasis risk. Validationin other sample sets of similar characteristics is warranted to bringfurther definition to the causal variant(s).

Materials and Methods

Clinical Samples

Three sample sets of psoriasis cases and unaffected controls wereassembled in this study. Detailed demographics and diagnostic/enrollmentcriteria have been described in a previous publication (Cargill, M.,Schrodi, S. J., Chang, M., Garcia, V. E., Brandon, R., Callis, K. P.,Matsunami, N., Ardlie, K. G., Civello, D., Catanese, J. J. et al. (2007)A large-scale genetic association study confirms IL12B and leads to theidentification of IL23R as psoriasis-risk genes. Am J Hum Genet, 80,273-390). Briefly, all individuals are North American whites of Europeandescent and were 18 years or older when they contributed their samples(sample set 1: 467 cases/460 controls; sample set 2: 498 cases/498controls; sample set 3: 483 cases/427 controls. Informed written consentwas obtained from all participants, and all protocols were approved bynational and/or local institutional review board.

Selection of Tagging SNPs and Overall Study Design

To comprehensively yet efficiently investigate the 5q31 region, we ranthe MIT tagger program (de Bakker, P. I., Yelensky, R., Pe'er, I.,Gabriel, S. B., Daly, M. J. and Altshuler, D. (2005) Efficiency andpower in genetic association studies. Nat Genet, 37, 1217-1223) with theCEU HapMap phase II dataset (The landmarks were set at chr5:131373131 .. . 132097638 [NCBI Build 36]; minimal allele frequency was set at 0.02;r² threshold was set at 0.8; and tagging mode was set at pair wise). Atotal of 103 tagging SNPs (including the previously tested IL13 markerrs20541) are required to capture the SNP diversity (610 polymorphicsites) within this 725 kbp region. Assay designs were attempted on thedefault tagging markers, and when not feasible, on an alternative markerwithin the tagging group. We also referenced the WTCCC study topreferentially select markers that were significantly associated with CDas tagging markers. We were able to develop assays for 90 of thesetagging SNPs (excluding the assay already available for rs20541). Inaddition, assays for two SNPs in predicted transcription factor bindingsites (rs381870 and rs4540166) were developed.

The above 92 SNPs were genotyped in one of the three psoriasiscase-control sample sets (sample set 1; 467 cases/460 controls).Genotyping data for 90 markers, including 88 tagging markers (equivalentto 86.4% coverage for all tagging markers), passed quality control andwere subjected to further analysis. Hardy-Weinberg equilibrium testsidentified six markers in controls and two others in cases with P<0.05(Table 12). However, analysis of the data showed no apparent error ingenotype assignment for these markers, thus they were included in theassociation tests. As predicted, inter-marker LD between the genotypedmarkers was low in our samples (FIG. 2B). Significant SNPs (P<0.05) werethen genotyped in two other case control sample sets (sample set 2 (498cases/498 controls) and sample set 3 (481 cases/424 controls)).

Genotyping

Genotyping was carried out by the method of real-time, allele-specificPCR with primers designed and validated in-house (Germer, S., Holland,M. J. and Higuchi, R. (2000) High-throughput SNP allele-frequencydetermination in pooled DNA samples by kinetic PCR. Genome Res, 10,258-266). Genotype calls of cases and controls, randomly arrayed ontogenotyping plates, were made using an automated algorithm and weresubjected to manual examination without knowledge of case-controlstatus, prior to statistical analysis. Our genotyping accuracy has beenconsistently better than 99% (Cargill, M., Schrodi, S. J., Chang, M.,Garcia, V. E., Brandon, R., Callis, K. P., Matsunami, N., Ardlie, K. G.,Civello, D., Catanese, J. J. et al. (2007) A large-scale geneticassociation study confirms IL12B and leads to the identification ofIL23R as psoriasis-risk genes. Am J Hum Genet, 80, 273-390; Li, Y.,Rowland, C., Catanese, J., Morris, J. C., Lovestone, S., O'Donovan M,C., Goate, A., Owen, M., Williams, J. and Grupe, A. (2008) SORL1variants and risk of late-onset Alzheimer's disease. Neurobiol Dis, 29,293-296).

Statistical Analysis

Hardy-Weinberg equilibrium was examined by an exact test. Allelicassociation of SNPs with psoriasis risk was determined by the χ² test inindividual sample sets and by meta-analysis using fixed effects ofMantel-Haenszel methods to combine odds ratios across the sample sets.Marker conditional association tests were done using an approach similarto the haplotype method (22) as previously described (Cargill, M.,Schrodi, S. J., Chang, M., Garcia, V. E., Brandon, R., Callis, K. P.,Matsunami, N., Ardlie, K. G., Civello, D., Catanese, J. J. et al. (2007)A large-scale genetic association study confirms IL12B and leads to theidentification of IL23R as psoriasis-risk genes. Am J Hum Genet, 80,273-390). In brief, cases and controls were partitioned on the basis ofgenotypes at one SNP, and counts at an interrogated SNP were subjectedto analysis where statistical significance was assessed by a permutationmethod (10,000 permutations). For marker-marker LD measurements, D′ andr² were calculated using LDMax. Haplotypes were estimated and tested forassociation with disease status using a score test with haplotypes codedin an additive fashion (Schaid, D. J., Rowland, C. M., Tines, D. E.,Jacobson, R. M. and Poland, G. A. (2002) Score tests for associationbetween traits and haplotypes when linkage phase is ambiguous. Am J HumGenet, 70, 425-434). Power calculations were done using the PS:Power andSample Size Calculation Program, obtained from the Department ofBiostatistics, Vanderbilt University website(http://biostat.mc.vanderbilt.edu/twiki/biniview/Main/PowerSampleSize).

Example Three: Additional LD SNPs Associated with Psoriasis

Additional investigation was conducted to identify SNPs in linkagedisequilibrium (LD) with certain “interrogated SNPs” which have beenfound to be associated with psoriasis, as shown in the tables. Theinterrogated SNPs, which are shown in column 1 (which indicates the hCVidentification numbers of each interrogated SNP) and column 2 (whichindicates the public rs identification numbers of each interrogated SNP)of Table 4. The methodology is described earlier in the instantapplication. To summarize briefly, the power threshold (T) was set at anappropriate level, such as 51%, for detecting disease association usingLD markers. This power threshold is based on equation (31) above, whichincorporates allele frequency data from previous disease associationstudies, the predicted error rate for not detecting trulydisease-associated markers, and a significance level of 0.05. Using thispower calculation and the sample size, for each interrogated SNP athreshold level of LD, or r² value, was derived (r_(T) ², equations (32)and (33) above). The threshold value r_(T) ² is the minimum value oflinkage disequilibrium between the interrogated SNP and its LD SNPspossible such that the non-interrogated SNP still retains a powergreater or equal to T for detecting disease-association.

Based on the above methodology, LD SNPs were found for the interrogatedSNPs. Several exemplary LD SNPs for the interrogated SNPs are listed inTable 4; each LD SNP is associated with its respective interrogated SNP.Also shown are the public SNP IDs (rs numbers) for the interrogated andLD SNPs, when available, and the threshold r² value and the power usedto determine this, and the r² value of linkage disequilibrium betweenthe interrogated SNP and its matching LD SNP. As an example in Table 4,the interrogated, psoriasis-associated SNP rs20541 (hCV2259921) wascalculated to be in LD with rs847 (hCV8932046) at an r² value of 0.9061,based on a 51% power calculation, thus establishing the latter as amarker associated with psoriasis as well.

All publications and patents cited in this specification are hereinincorporated by reference in their entirety. Various modifications andvariations of the described compositions, methods and systems of theinvention will be apparent to those skilled in the art without departingfrom the scope and spirit of the invention. Although the invention hasbeen described in connection with specific preferred embodiments andcertain working examples, it should be understood that the invention asclaimed should not be unduly limited to such specific embodiments.Indeed, various modifications of the above-described modes for carryingout the invention that are obvious to those skilled in the field ofmolecular biology, genetics and related fields are intended to be withinthe scope of the following claims.

TABLE 1 Transcript SNP info and associated gene/protein informationGene Number: 1 Gene Symbol IL13 - 3596 Gene Name: interleukin 13Transcript Accession: NM_002188 Protein Accession: NP_002179 Chromosome:5 OMIM NUMBER: 147683 OMIM Information:{Asthma, susceptibility to}, 600807 (3);{Allergic rhinitis,/susceptibility to}, 607154 (3)Transcript Sequence (SEQ ID NO: 1): Protein Sequence (SEQ ID NO: 3):SNP Information Context (SEQ ID NO: 5):GGCAGTTTTCCAGCTTGCATGTCCGAGACACCAAAATCGAGGTGGCCCAGTTTGTAAAGGACCTGCTCTTACATTTAAAGAAACTTTTTCGCGAGGGACA RTTCAACTGAAACTTCGAAAGCATCATTATTTGCAGAGACAGGACCTGACTATTGAAGTTGCAGATTCATTTTTCTTTCTGATGTCAAAAATGTCTTGGGT Celera SNP ID: hCV2259921Public SNP ID: rs20541 SNP Chromosome Position: 132023863SNP in Transcript Sequence SEQ ID NO: 1 SNP Position Transcript: 446SNP Source: Applera Population (Allele, Count):Caucasian (A, 6|G, 34) African American (A, 7|G, 29) total (A, 13|G, 63)SNP Type: Missense Mutation Protein Coding:SEQ ID NO: 3, at position 144, (Q, CAG) (R, CGG) SNP Source:HGMD; dbSNP; HapMap; HGBASE Population (Allele, Count):Caucasian (A, 28|G, 92) SNP Type: Missense Mutation Protein Coding:SEQ ID NO: 3, at position 144, (Q, CAG) (R, CGG) Context (SEQ ID NO: 6):GAGTGTGTTTGTCACCGTTGGGGATTGGGGAAGACTGTGGCTGCTAGCACTTGGAGCCAAGGGTTCAGAGACTCAGGGCCCCAGCACTAAAGCAGTGGAC MCCAGGAGTCCCTGGTAATAAGTACTGTGTACAGAATTCTGCTACCTCACTGGGGTCCTGGGGCCTCGGAGCCTCATCCGAGGCAGGGTCAGGAGAGGGGC Celera SNP ID: hCV8932051Public SNP ID: rs848 SNP Chromosome Position: 132024399SNP in Transcript Sequence SEQ ID NO: 1 SNP Position Transcript: 981SNP Source: dbSNP; Celera; HapMap; HGBASE Population (Allele, Count):Caucasian (A, 29|C, 91) SNP Type: UTR3 Context (SEQ ID NO: 7):AGCCTCATCCGAGGCAGGGTCAGGAGAGGGGCAGAACAGCCGCTCCTGTCTGCCAGCCAGCAGCCAGCTCTCAGCCAACGAGTAATTTATTGTTTTTCCT YGTATTTAAATATTAAATATGTTAGCAAAGAGTTAATATATAGAAGGGTACCTTGAACACTGGGGGAGGGGACATTGAACAAGTTGTTTCATTGACTATCA Celera SNP ID: hCV8932046Public SNP ID: rs847 SNP Chromosome Position: 132024568SNP in Transcript Sequence SEQ ID NO: 1 SNP Position Transcript: 1150Related Interrogated SNP: hCV2259921 (Power = .51)Related Interrogated SNP: hCV8932051 (Power = .51) SNP Source:dbSNP; Celera; HapMap; HGBASE Population (Allele, Count):Caucasian (T, 27|C, 91) SNP Type: UTR3 Context (SEQ ID NO: 8):AGCAGCTCAGGCACACTTCTTCTTGGTCTTATTTATTATTGTGTGTTATTTAAATGAGTGTGTTTGTCACCGTTGGGGATTGGGGAAGACTGTGGCTGCT RGCACTTGGAGCCAAGGGTTCAGAGACTCAGGGCCCCAGCACTAAAGCAGTGGACACCAGGAGTCCCTGGTAATAAGTACTGTGTACAGAATTCTGCTACC Celera SNP ID: hCV8932052Public SNP ID: rs1295685 SNP Chromosome Position: 132024344SNP in Transcript Sequence SEQ ID NO: 1 SNP Position Transcript: 926Related Interrogated SNP: hCV2259921 (Power = .51)Related Interrogated SNP: hCV8932051 (Power = .51) SNP Source:dbSNP; Celera; HapMap; HGBASE Population (Allele, Count):Caucasian (A, 29|G, 91) SNP Type: UTR3 Gene Number: 2 Gene SymbolKIF3A - 11127 Gene Name: kinesin family member 3A Transcript Accession:NM_007054 Protein Accession: NP_008985 Chromosome: 5 OMIM NUMBER: 604683OMIM Information: Transcript Sequence (SEQ ID NO: 2):Protein Sequence (SEQ ID NO: 4): SNP Information Context (SEQ ID NO: 9):TTGAGACTTTATAAGTTAGTATTTATTAAATTAATATTATTTTAATAAGTTTTGTTAAATCCTAGTTTAAATGACAAAGCTGTGTATAGAGTAGGGGTGA STGAAGGTGGAGTACTCTTGAGGTGGCGATAAAAATGTACCCATAAATTTAAAGTCCATTCTGTAATTGGAATACTGAATGTCCTGTGTGTGGTGAACATT Celera SNP ID: hCV11818506Public SNP ID: rs17690965 SNP Chromosome Position: 132058566SNP in Transcript Sequence SEQ ID NO: 2 SNP Position Transcript: 3913Related Interrogated SNP: hCV16176374 (Power = .6) SNP Source:dbSNP; Celera; HapMap Population (Allele, Count):Gaucasian (G, 31|C, 69) SNP Type: UTR3

TABLE 2 Genomic SNP info and associated gene information Gene Number: 1Gene Symbol: IL13 - 3596 Gene Name: interleukin 13 Chromosome: 5OMIM NUMBER: 147683 OMIM Information:{Asthma, susceptibility to}, 600807 (3); {Allergic rhinitis, /susceptibility to}, 607154 (3)Genomic Sequence (SEQ ID NO: 10): SNP InformationContext (SEQ ID NO: 19):CAGCAGTTTTCCAGCTTGCATGTCCGAGACACCAAAATCGAGGTGGCCCAGTTTGTAAAGGACCTGCTCTTACATTTAAAGAAACTTTTTCGCGAGGGAC RGTTCAACTGAAACTTCGAAAGCATCATTATTTGCAGAGACAGGACCTGACTATTGAAGTTGCAGATTCATTTTTCTTTCTGATGTCAAAAATGTCTTGGG Celera SNP ID: hCV2259921Public SNP ID: rs20541 SNP Chromosome Position: 132023863SNP in Genomic Sequence: SEQ ID NO: 10 SNP Position Genomic: 12099SNP Source: Applera Population (Allele, Count):Caucasian (A, 6|G, 34) African American (A, 7|G, 29) total (A, 13|G, 63)SNP Type: MISSENSE MUTATION; ESE; UTR3; SILENT RARE CODON; SILENTMUTATION SNP Source: HGMD; dbSNP; HapMap; HGBASEPopulation (Allele, Count): Caucasian (A, 28|G, 92) SNP Type:MISSENSE MUTATION; ESE; UTR3; SILENT RARE CODON; SILENT MUTATIONContext (SEQ ID NO: 20):TATTCTAAATACTTGAAAACTTTAAATGTATTCATTCCTCAGAGCAACTTCATGAGACAGGGACAGCTATGACCCCTATTTCACAGATGAGGCTGAGTAG MGTGCCCAAGGTCACACAGCCAGGAGGCACAGCAGCCAGGCCTGACAGACCACCTGGGCCCAGCGTCCGCTCTCTTAGCCACCGTGTACTATAGCAGCCTC Celera SNP ID: hCV2259917Public SNP ID: rs762534 SNP Chromosome Position: 132032655SNP in Genomic Sequence: SEQ ID NO: 10 SNP Position Genomic: 20891SNP Source: dbSNP; Celera; HapMap; ABI_Val; HGBASEPopulation (Allele, Count): Caucasian (C, 111|A, 9) SNP Type:INTERGENIC; UNKNOWN Context (SEQ ID NO: 21):GAGTGTGTTTGTCACCGTTGGGGATTGGGGAAGACTGTGGCTGCTAGCACTTGGAGCCAAGGGTTCAGAGACTCAGGGCCCCAGCACTAAAGCAGTGGAC MCCAGGAGTCCCTGGTAATAAGTACTGTGTACAGAATTCTGCTACCTCACTGGGGTCCTGGGGCCTCGGAGCCTCATCCGAGGCAGGGTCAGGAGAGGGGC Celera SNP ID: hCV8932051Public SNP ID: rs848 SNP Chromosome Position: 132024399SNP in Genomic Sequence: SEQ ID NO: 10 SNP Position Genomic: 12635SNP Source: dbSNP; Celera; HapMap; HGBASE Population (Allele, Count):Caucasian (A, 29|C, 91) SNP Type: UTR3 Context (SEQ ID NO: 22):TCGGGGAGGAAGTGGGTAGGGGAGAAATCTTGACATCAACACCCAACAGGCAAATGCCGTGGCCTCTGCTGTGGGGGTTTCTGGAGGACTTCTAGGAAAA YGAGGGAAGAGCAGGAAAAGGCGACATGGCTGCAGGGGCCAAGCCCAGGAGCCGCCCTCCACAGCACTCATTCTGCAGAAGGGAAATTTGAGGCCCCCAGA Celera SNP ID: hCV50000065Public SNP ID: rs1800925 SNP Chromosome Position: 132020708SNP in Genomic Sequence: SEQ ID NO: 10 SNP Position Genomic: 8944SNP Source: dbSNP; HGBASE Population (Allele, Count):Caucasian (C, 97|T, 23) SNP Type: MISSENSE MUTATION; UTR5; INTRONContext (SEQ ID NO: 23):CACAGCAGGGAGAGTGCTGTGTTATGCGAGGAGGTTGGAGAAATCCTCCCCATGAGATAAGATGGGAACAGAGATCGGGACGAAACAAGGGGAGGGGACA MCCATGCACAGATCGGGGCAAAGTCATCAAGGGAAAGGGAACTGCAGGTGCTAAGGTCTTGAGCAAGAGCGAGCTGGGGATGCCCTTCCCAGCACTCACGG Celera SNP ID: hCV16176063Public SNP ID: rs2243211 SNP Chromosome Position: 132029321SNP in Genomic Sequence: SEQ ID NO: 10 SNP Position Genomic: 17557SNP Source: dbSNP; HapMap; HGBASE Population (Allele, Count):Caucasian (C, 108|A, 12) SNP Type: TFBS SYNONYMOUS; INTERGENIC; UNKNOWNContext (SEQ ID NO: 24):CAGTACCCACCTCATGGGGACTTCCGTGAGGACTGAATGAGACAGTCCCTGGAAAGCCCCTGGTTTGTGCGAGTCGTCCCGGCCTCTGGCGTTCTACTCA YGTGCTGACCTCTTTGTCCTGCAGCAGTTTTCCAGCTTGCATGTCCGAGACACCAAAATCGAGGTGGCCCAGTTTGTAAAGGACCTGCTCTTACATTTAAA Celera SNP ID: hCV8932053Public SNP ID: rs1295686 SNP Chromosome Position: 132023742SNP in Genomic Sequence: SEQ ID NO: 10 SNP Position Genomic: 11978Related Interrogated SNP: hCV2259921 (Power = .51)Related Interrogated SNP: hCV8932051 (Power = .51) SNP Source: AppleraPopulation (Allele, Count):Caucasian (C, 33|T, 7) African American (C, 13|T, 23) total (C, 46|T, 30)SNP Type: TRANSCRIPTION FACTOR BINDING SITE; INTRON SNP Source:dbSNP; HapMap; ABI_Val; HGBASE Population (Allele, Count):Caucasian (T, 28|C, 92) SNP Type:TRANSCRIPTION FACTOR BINDING SITE; INTRON Context (SEQ ID NO: 25):AGCCTCATCCGAGGCAGGGTCAGGAGAGGGGCAGAACAGCCGCTCCTGTCTGCCAGCCAGCAGCCAGCTCTCAGCCAACGAGTAATTTATTGTTTTTCCT YGTATTTAAATATTAAATATGTTAGCAAAGAGTTAATATATAGAAGGGTACCTTGAACACTGGGGGAGGGGACATTGAACAAGTTGTTTCATTGACTATCA Celera SNP ID: hCV8932046Public SNP ID: rs847 SNP Chromosome Position: 132024568SNP in Genomic Sequence: SEQ ID NO: 10 SNP Position Genomic: 12804Related Interrogated SNP: hCV2259921 (Power = .51)Related Interrogated SNP: hCV8932051 (Power = .51) SNP Source:dbSNP; Celera; HapMap; HGBASE Population (Allele, Count):Caucasian (T, 27|C, 91) SNP Type: MICRORNA; UTR3Context (SEQ ID NO: 26):AGCAGCTCAGGCACACTTCTTCTTGGTCTTATTTATTATTGTGTGTTATTTAAATGAGTGTGTTTGTCACCGTTGGGGATTGGGGAAGACTGTGGCTGCT RGCACTTGGAGCCAAGGGTTCAGAGACTCAGGGCCCCAGCACTAAAGCAGTGGACACCAGGAGTCCCTGGTAATAAGTACTGTGTACAGAATTCTGCTACC Celera SNP ID: hCV8932052Public SNP ID: rs1295685 SNP Chromosome Position: 132024344SNP in Genomic Sequence: SEQ ID NO: 10 SNP Position Genomic: 12580Related Interrogated SNP: hCV2259921 (Power = .51)Related Interrogated SNP: hCV8932051 (Power = .51) SNP Source:dbSNP; Celera; HapMap; HGBASE Population (Allele, Count):Caucasian (A, 29|G, 91) SNP Type: MICRORNA; UTR3Context (SEQ ID NO: 27):GAGGTGTTATAGTGCCAGGGAAAAGGGGTGCAAGACTAGTGTTTGCCTCTTATTTCTTGTCTTGTTTATAAATTCTCTACATTAAAAATATAAATTCCAA RTGAAAACAATGGAATAAACACAAACTCCCACTTTATAACCAACTAAAATGACAGTAACTGAATTTTCTAAAGTTTTAAACCCACCAAAATGGGAGAAATG Celera SNP ID: hCV27452177Public SNP ID: rs3091307 SNP Chromosome Position: 132017035SNP in Genomic Sequence: SEQ ID NO: 10 SNP Position Genomic: 5271Related Interrogated SNP: hCV50000065 (Power = .51) SNP Source:dbSNP; HapMap; ABI_Val; HGBASE Population (Allele, Count):Caucasian (A, 94|G, 26) SNP Type: INTRON Gene Number: 2 Gene Symbol:KIF3A - 11127 Gene Name: kinesin family member 3A Chromosome: 5OMIM NUMBER: 604683 OMIM Information: Genomic Sequence (SEQ ID NO: 11):SNP Information Context (SEQ ID NO: 28):AATAGGCTTTAACTCTTTATGACAAAATTATGTAAAAAACTCTAGGGTTTAAAATACATTATTTGTATAGAACTGTAAGTCCAGAGCAAACCTAAGACAC RAGACAAATGAAATAAAAGAGTAAATAAAAGCACTGATCCAAATTCATGCTTTGGTGTGGTGTGATTCATTGCATTCCAAAAGTCAGGATGTAGACTGATT Celera SNP ID: hCV29575948Public SNP ID: rs10069772 SNP Chromosome Position: 132068587SNP in Genomic Sequence: SEQ ID NO: 11 SNP Position Genomic: 22365SNP Source: dbSNP; HapMap Population (Allele, Count):Caucasian (A, 16|G, 104) SNP Type: INTRON Context (SEQ ID NO: 29):ACAGTTGCTGAGCTGTCAAGATATATCATCATACACTAAAGGAACAACTAAAATAGCTTGTTATTATGTCAAACTCAGGACCCGAAGGCTCCCTAAGTCA RAGTAAACATGCCAAGTGTCAAATATAAGTAGAAATACTACCAAATAATAAAGCTGGAATATGGCTTCCAATTGATTATTTTTGCTAATAATGTCTAATAA Celera SNP ID: hCV31237680Public SNP ID: rs12186803 SNP Chromosome Position: 132067968SNP in Genomic Sequence: SEQ ID NO: 11 SNP Position Genomic: 21746SNP Source: dbSNP; HapMap Population (Allele, Count):Caucasian (G, 101|A, 19) SNP Type:TRANSCRIPTION FACTOR BINDING SITE; INTRON Context (SEQ ID NO: 30):TCACCCTCTTCATCATCATCTTCCTCTGACCCACTGATATCAGAGCCTGATATTTCTTCTCCTTGGACAGAAATTTAATACAATGTTTTTTATCCTGTAC SAAGTCATTAGCTATTTAGGAAATACCTATATCAGCTTTCTTCCTCAGATTTTTGTTACTGCAAACAACAAATTTAAATACTATTTAAATGCTCCTAGAAA Celera SNP ID: hCV11818501Public SNP ID: rs41564665 SNP Chromosome Position: 132074688SNP in Genomic Sequence: SEQ ID NO: 11 SNP Position Genomic: 28466Related Interrogated SNP: hCV16176374 (Power = .6) SNP Source: AppleraPopulation (Allele, Count):Caucasian (C, 30|G, 10) African American (C, 14|G, 20) total (C, 44|G, 30)SNP Type: INTRON SNP Source: dbSNP; Celera; HapMapPopulation (Allele, Count): Caucasian (G, 34|C, 86) SNP Type: INTRONContext (SEQ ID NO: 31):AAGGGTGTTCTAAAGCTGGATTGTGATGATGGTTTCACAACTGTATATATTTACTACACTCATCAAACTGCACAGCTGCAATATGTGAATTTATGGCACA KTAATTATGTCTCAATAAGGGAGTTTTTTAAAAAGTAAAGATTCACTTACCATTGTAGCCTTCAAGTACAGAATCAATAATAGGTCTTGCAGTTAAGTTAT Celera SNP ID: hCV2558119Public SNP ID: rs9784600 SNP Chromosome Position: 132097746SNP in Genomic Sequence: SEQ ID NO: 11 SNP Position Genomic: 51524Related Interrogated SNP: hCV16176374 (Power = .51) SNP Source:dbSNP; Celera Population (Allele, Count): Caucasian (G, 95|T, 21)SNP Type: INTRON Context (SEQ ID NO: 32):ATTAATGGAAGAGAGTTCTGAAATAAATATTTATGGTAAAAAGGTTTGAAATGTAGGCCATTATAATATGTCCATTTCATTTGCATATTATCTATATTCT KATCATAATAAACAGTCTTAATTCACACGTGGCAACAAATCCCCCACAACAGAGTGAGAATGAGAATACATTTTATAAAGAAAAAGAACTAAATTTAAAAA Celera SNP ID: hCV2558124Public SNP ID: rs10036532 SNP Chromosome Position: 132073714SNP in Genomic Sequence: SEQ ID NO: 11 SNP Position Genomic: 27492Related Interrogated SNP: hCV16176374 (Power = .6) SNP Source:dbSNP; Celera; HapMap Population (Allele,Count): Caucasian (G, 33|T, 81)SNP Type: TRANSCRIPTION FACTOR BINDING SITE; INTRONContext (SEQ ID NO: 33):TTTCCTTTTAAAAGGGTGAAAGATAGCCTATTTTTAATATTTAATAACATCTAAAATATTGAAGTCATAAAACTAAAATCTTAATAACATTGAGTAATAA WAGTCTCAAAACATTATATACTGATATAACCTTTTTATAAATTCTAAAATACATATTTCTTAGGAATGCATGCAGATGAAATAAAACTAAATGAAAATGAA Celera SNP ID: hCV8932022Public SNP ID: rs1468215 SNP Chromosome Position: 132064388SNP in Genomic Sequence: SEQ ID NO: 11 SNP Position Genomic: 18166Related Interrogated SNP: hCV16176374 (Power = .6) SNP Source:dbSNP; HapMap; HGBASE Population (Allele, Count):Caucasian (T, 34|A, 86) SNP Type:TRANSCRIPTION FACTOR BINDING SITE; INTRON Context (SEQ ID NO: 34):TCTGAGGTACTCAAAAGGTGCAAGTGGATTCAGAGGAAATCAGAAACAAATCATCTCAGGCAATACCTGATGCATATGTAGGGACTTATGGAAATGCTAC RTTAATGTATTATATTTATTGCAATTTTGCCTAGCCCATCTAACTATGTGTTTCTAACAAGGAACATCACATTGAACATATCATATAATGTAACATAGCAT Celera SNP ID: hCV11740439Public SNP ID: rs2023823 SNP Chromosome Position: 132060705SNP in Genomic Sequence: SEQ ID NO: 11 SNP Position Genomic: 14483Related Interrogated SNP: hCV16176374 (Power = .6) SNP Source:dbSNP; HapMap; HGBASE Population (Allele, Count):Caucasian (A, 34|G, 82) SNP Type: INTRON Context (SEQ ID NO: 35):TTAAAAATTATTATTTTAATGCTATTGCCTACTTTTTTATTGTTGATATGATCAACTCCATTAACTAGATTATAAAAAGAAATGTCATAAGAGCAAAAAT RAACTGAAATGTATTAACAACAGTATTATCATAGAATCCAGCAATTCCATTGCTGGGTACATACCCCAAAAATGGTAAAACAAGAATTCAAACAGGTATTA Celera SNP ID: hCV11818497Public SNP ID: rs4266392 SNP Chromosome Position: 132077154SNP in Genomic Sequence: SEQ ID NO: 11 SNP Position Genomic: 30932Related Interrogated SNP: hCV16176374 (Power = .6) SNP Source:dbSNP; Celera; HapMap; HGBASE Population (Allele, Count):Caucasian (G, 35|A, 85) SNP Type:TRANSCRIPTION FACTOR BINDING SITE; INTRON Context (SEQ ID NO: 36):AAGGAAAACTGGCCAAATTTGAATAAAGTCCACAGATTAGTTAATAAGACTATATCAATGTAAATCTCCTGGTTTCAATAACTGTTGTATGCTTATAAAA RATGTTAACATGAGGTGAAGCTGGGTGAAGGGTAGATAGGAACTCTCCATATCATGTTTGCAAGTTGCATATAGCCTACAATAATTTTTAAGTTTAAAAAT Celera SNP ID: hCV11818498Public SNP ID: rs4425499 SNP Chromosome Position: 132076961SNP in Genomic Sequence: SEQ ID NO: 11 SNP Position Genomic: 30739Related Interrogated SNP: hCV16176374 (Power = .6) SNP Source:dbSNP; Celera; HapMap; HGBASE Population (Allele, Count):Caucasian (A, 34|G, 86) SNP Type: INTRON Context (SEQ ID NO: 37):GGATTGTATCCTGGACCAGGAAAAAGAGGCACTGGAAGGAAAACTGGCCAAATTTGAATAAAGTCCACAGATTAGTTAATAAGACTATATCAATGTAAAT YTCCTGGTTTCAATAACTGTTGTATGCTTATAAAAAATGTTAACATGAGGTGAAGCTGGGTGAAGGGTAGATAGGAACTCTCCATATCATGTTTGCAAGTT Celera SNP ID: hCV11818499Public SNP ID: rs2897442 SNP Chromosome Position: 132076926SNP in Genomic Sequence: SEQ ID NO: 11 SNP Position Genomic: 30704Related Interrogated SNP: hCV16176374 (Power = .6) SNP Source:dbSNP; Celera; HapMap; HGBASE Population (Allele, Count):Caucasian (C, 35|T, 85) SNP Type: INTRON Context (SEQ ID NO: 38):AATGTTCACCACACACAGGACATTCAGTATTCCAATTACAGAATGGACTTTAAATTTATGGGTACATTTTTATCGCCACCTCAAGAGTACTCCACCTTCA STCACCCCTACTCTATACACAGCTTTGTCATTTAAACTAGGATTTAACAAAACTTATTAAAATAATATTAATTTAATAAATACTAACTTATAAAGTCTCAA Celera SNP ID: hCV11818506Public SNP ID: rs17690965 SNP Chromosome Position: 132058566SNP in Genomic Sequence: SEQ ID NO: 11 SNP Position Genomic: 12344Related Interrogated SNP: hCV16176374 (Power = .6) SNP Source:dbSNP; Celera; HapMap Population (Allele, Count):Caucasian (C, 31|G, 69) SNP Type: MICRORNA; UTR3; INTRONContext (SEQ ID NO: 39):TAGATTACAGTAATTTCCACTGATTATTTGATTAACAGAAAGGTCTAATGAAGAATTTTTAAAGACACAAGTTCTCCCAATACATCCGATTTCCCAACCG KATTAAGGGCTTTTTTTTTTTTCCAGAAAATAAAATTATTACATAAAATGAAGTATACCTGTACAGTAACAAACTTACATTCCTTCTATTAGTAGATTTTT Celera SNP ID: hCV15751509Public SNP ID: rs2299009 SNP Chromosome Position: 132070712SNP in Genomic Sequence: SEQ ID NO: 11 SNP Position Genomic: 24490Related Interrogated SNP: hCV16176374 (Power = .6) SNP Source:dbSNP; HapMap; HGBASE Population (Allele, Count):Caucasian (G, 35|T, 85) SNP Type: INTRON Context (SEQ ID NO: 40):GGCCAGGATGGTCTCAATCTCTTGACCTCGTGATCCACCTGCCTCAACCTCCCAAAGTGCTGGGATTACAGGGGTGAGCCACCACACCCGGCCCAGCAGT WGTTTTTCTAAAACACAAATAGGCCAGGTGCAGTGGCTCACGCCTGTAATCCCGGCACTTTGGGAGACTGAGATGGGAGCTTCGCTTGAACCCAAAAGTTC Celera SNP ID: hCV15793498Public SNP ID: rs2406539 SNP Chromosome Position: 132051175SNP in Genomic Sequence: SEQ ID NO: 11 SNP Position Genomic: 4953Related Interrogated SNP: hCV16176374 (Power = .7) SNP Source:dbSNP; HapMap; HGBASE Population (Allele, Count):Caucasian (A, 29|T, 77) SNP Type:TRANSCRIPTION FACTOR BINDING SITE; INTERGENIC; UNKNOWNContext (SEQ ID NO: 41):AGAGAATAGCAGCCACTCACTTTAGACAGGACTGCTCACCACTGCCAATTTTTCTCCTACGCTGGGGACAAATGTCTTACCATTTATCATCACACTTGCA YTGTCATTTTATTAAAAATGGAAAAAAAGATACATCTAAAGGGACTCATGTTTCTTAGAACTGATTTGCTTCACTACAATATGCTTGGCATGTGTTGGTAT Celera SNP ID: hCV15955623Public SNP ID: rs2237059 SNP Chromosome Position: 132061511SNP in Genomic Sequence: SEQ ID NO: 11 SNP Position Genomic: 15289Related Interrogated SNP: hCV16176374 (Power = .51) SNP Source:dbSNP; HapMap; ABI_Val; HGBASE Population (Allele, Count):Caucasian (C, 96|T, 20) SNP Type: INTRON Context (SEQ ID NO: 42):ACCAAGAGACAGCCGTATGAGAGTTGCATAGATTGGCGCTACTAAAAAGAAACAAAATTTTGCTCGGCATGGAAAATGATTTGTGGTATCTTTCATTCAT MTATGCTCTCTACATGGTAAATAATCAAAGTGGAATGGTTTTCAAGAAACCTAAAAAATCCAGTCTCTACAGGGTAAAGTGCCATACCAAATTTGCTTCTA Celera SNP ID: hCV16164369Public SNP ID: rs41564561 SNP Chromosome Position: 132084046SNP in Genomic Sequence: SEQ ID NO: 11 SNP Position Genomic: 37824Related Interrogated SNP: hCV16176374 (Power = .6) SNP Source:dbSNP; HapMap; ABI_Val; HGBASE Population (Allele, Count):Caucasian (C, 35|A, 85) SNP Type: INTRON Context (SEQ ID NO: 43):AAAATAGCTACACTGGAGACAAAAATCCAAGCTTTTAATTACTATTCAATTTTCCTATTTTATATATCCTAGGAAAAAACAGAAATTTAAATCATGAATT MATCTCAATTCAATAATACTCACTGGGCTTTAAGAAGATCTTTTTCCCGTTTCTCTAATTCAGCTCTAGCCTTGTTTCTTTCTTCTTCTTCCATGTCGAGC Celera SNP ID: hCV16177653Public SNP ID: rs2285700 SNP Chromosome Position: 132067031SNP in Genomic Sequence: SEQ ID NO: 11 SNP Position Genomic: 20809Related Interrogated SNP: hCV16176374 (Power = .6) SNP Source:dbSNP; HapMap; ABI_Val; HGBASE Population (Allele, Count):Caucasian (C, 34|A, 86) SNP Type:TRANSCRIPTION FACTOR BINDING SITE; INTRON Context (SEQ ID NO: 44):ACTGGGTTTCTAAATACCATTCTCCTACAGAAGGGACCAGAGAGAAGTGAATGATTCTAAGATTGGGCAAGGAAGACACAAGATAAACCTAAAACCTTTT RTAGTGCCAAAAAGTAATCAAATGCTCAAAAAAACTGATGAGCACATGCTGAAAGAATACAGGAACTACTCTGAAGGATCTCATAATAGCCAAAGCTGGAA Celera SNP ID: hCV26478846Public SNP ID: rs6864565 SNP Chromosome Position: 132075870SNP in Genomic Sequence: SEQ ID NO: 11 SNP Position Genomic: 29648Related Interrogated SNP: hCV16176374 (Power = .6) SNP Source:dbSNP; Celera; HapMap Population (Allele, Count):Caucasian (G, 34|A, 86) SNP Type:TRANSCRIPTION FACTOR BINDING SITE; INTRON Context (SEQ ID NO: 45):CAGAGTCTTGGGAGAAGAAATTTCTGAAAAATATTTTTTTCTTCGGGCTTAGAAACAATGACATCTTGGTAGTAATGAGCACAGCTAGTGCCCAAAACTG SGTTTCTAAATACCATTCTCCTACAGAAGGGACCAGAGAGAAGTGAATGATTCTAAGATTGGGCAAGGAAGACACAAGATAAACCTAAAACCTTTTGTAGT Celera SNP ID: hCV26478847Public SNP ID: rs6864396 SNP Chromosome Position: 132075774SNP in Genomic Sequence: SEQ ID NO: 11 SNP Position Genomic: 29552Related Interrogated SNP: hCV16176374 (Power = .6) SNP Source:dbSNP; Celera; HapMap Population (Allele, Count):Caucasian (G, 34|C, 86) SNP Type: INTRON Context (SEQ ID NO: 46):TCTTCCTAGTCCAACTTTAAGTCTCTAAGCTGTCTGTTCCTTCTAGTTTCTGATTAGCCAGAGTTCAGCCAAACGAAAATATGTTTTGATGTTTTGTATG STCACTGCACACCTGGGTACTTACTAGGCAACGTGAATAAGAGGACACACATTTGCTCCCTCAGTTTATACCAATCACGAGTGCAAGCAAAACAGCTGAGA Celera SNP ID: hCV26478954Public SNP ID: rs4426908 SNP Chromosome Position: 132050617SNP in Genomic Sequence: SEQ ID NO: 11 SNP Position Genomic: 4395Related Interrogated SNP: hCV16176374 (Power = .7) SNP Source:dbSNP; Celera; HGBASE Population (Allele, Count):Caucasian (C, 32|G, 88) SNP Type:TRANSCRIPTION FACTOR BINDING SITE; INTERGENIC; UNKNOWNContext (SEQ ID NO: 47):AATAGATAAAATTAAAAATTGCACATAAAGAAATATTTTATTTCTTTTAAATTATAAGCTCACATTATGATTATTTATAAATTCTTAATCAAAGAACTCC YTTTTAAAAAATCCAGAACTGCATTAGTAGGTAATTTCTAAGAGAACCAACCTCTGACTTTGCAGCCATCAGCATAGTCCAAACTTTCTTTAACTTCTTGG Celera SNP ID: hCV27472356Public SNP ID: rs3213639 SNP Chromosome Position: 132066098SNP in Genomic Sequence: SEQ ID NO: 11 SNP Position Genomic: 19876Related Interrogated SNP: hCV16176374 (Power = .6) SNP Source:dbSNP; HapMap; HGBASE Population (Allele, Count):Caucasian (C, 34|T, 86) SNP Type: INTRON Context (SEQ ID NO: 48):TGGTGATGAAACTGAATCAAAGACAATTCATTTCTGGTCATACAGTTTCTTAGAAACATACATTCCTTCAGAAAACCAATAACACTTTTCACAGAATTGG WCTGAGGCTCTCCTAGAACCTTTCCGTCATTCTTAACTTCCTTCCCAAAGAACTACAGAAGAAGAGTGTAAATCATAAGAGTGTATAAATTGTTAATGTCT Celera SNP ID: hCV30585769Public SNP ID: rs10062446 SNP Chromosome Position: 132068273SNP in Genomic Sequence: SEQ ID NO: 11 SNP Position Genomic: 22051Related Interrogated SNP: hCV16176374 (Power = .6) SNP Source:dbSNP; HapMap Population (Allele, Count): Caucasian (T, 34|A, 86)SNP Type: INTRON Context (SEQ ID NO: 49):TCTAAAAAGGGATGGGGGAGGGGAGCAGGTGGAGAGGAATATCTGATCTGTCATATTCTTTAGTCAGAGCCATAAACGTGTTTGGGTGAGACAATCTGAT STTCTGATAACGTTGATAAAAGTCACTTGAAGATTGGGTCACAGGAAGCCCAAGATAAATGCTGAGAGGAAACAGGTTCTTTTTGAAGTAGCCTCTTCGTA Celera SNP ID: hCV31237737Public SNP ID: rs11242122 SNP Chromosome Position: 132052607SNP in Genomic Sequence: SEQ ID NO: 11 SNP Position Genomic: 6385Related Interrogated SNP: hCV16176374 (Power = .7) SNP Source:dbSNP; HapMap; ABI_Val Population (Allele, Count):Caucasian (C, 31|G, 89) SNP Type: INTERGENIC; UNKNOWNContext (SEQ ID NO: 50):AAACAAGTGATCCACCCACCTCAGCCTCCCAAAGTGCTGGGATTACAGGTGTGAGCCACCGCGACCAGACTTTTCACCTCTAATTTCTAATTGCTATTAG YTGCATCACCAGTACTAGGTTTGAGGCATCTGTATAATATCGCTGAAGCTTCCTACTCTTTAGACTAAAAATGTGACACAATTACTAAAAAGAATACAATT Celera SNP ID: hCV31237618Public SNP ID: rs11242127 SNP Chromosome Position: 132083403SNP in Genomic Sequence: SEQ ID NO: 11 SNP Position Genomic: 37181Related Interrogated SNP: hCV16176374 (Power = .6) SNP Source: dbSNPPopulation (Allele, Count): Caucasian (C, 35|T, 85) SNP Type: INTRONContext (SEQ ID NO: 51):TACACTTAAAACAGGGCACATGCTGGGCACAGTGGCTCACGCCTGTAACCTCAGCACTTTGGGAGCCCAAGGCGGGAGGACTGCTTGAAGCCAGGAGTTC YAAACCAACCTGGGCAACTTAGCAAGCTCCTATCTCTACAAAAAATTAAAAAATTAGCCAAGTGTAGTGGCAGACACCTGTGGTCCCAGCTACTTGGGAGG Celera SNP ID: hCV31237741Public SNP ID: rs11747814 SNP Chromosome Position: 132052065SNP in Genomic Sequence: SEQ ID NO: 11 SNP Position Genomic: 5843Related Interrogated SNP: hCV16176374 (Power = .7) SNP Source:dbSNP; HapMap Population (Allele, Count): Caucasian (C, 31|T, 89)SNP Type: INTERGENIC; UNKNOWN Context (SEQ ID NO: 52):TGTGGGGAAACAGAGGGCTGGAGTAGTTGGTCAGGACACAGTGTAGTAAGAAAAGATAGCCTTGGATGTGATGGCATATATGAAAACGGTTCCTCAACTA WTACTACTCTATTCAGTTAACCTCAACTTTTCTCAGACTTTTTTTTGTGAAAATAATCATAACACACTTTTCAGACTTTTCCGTGAAAATAAATGAATCAT Celera SNP ID: hCV31237596Public SNP ID: rs3798129 SNP Chromosome Position: 132091459SNP in Genomic Sequence: SEQ ID NO: 11 SNP Position Genomic: 45237Related Interrogated SNP: hCV16176374 (Power = .51) SNP Source:dbSNP; HapMap; ABI_Val; HGBASE Population (Allele, Count):Caucasian (T, 99|A, 21) SNP Type: INTRON Context (SEQ ID NO: 53):TTCTATTAAGATTTGGTCTTTTTCTATTAATTGGTTCATAAGAATGTAATTGATTTTTGAAGTTTTGTTGTTTGATTTCCTTGGGTTTGATATATCTATC RTCAAGTCACAGAAACTTATAAAAATTTTTCATTTCCTATTTCTCATCTTTTACCTCTAATCCCTCTTTTTTTCTTTTTTTTTTGGTTGCTGTGTTGCCCA Celera SNP ID: hCV31237619Public SNP ID: rs4705965 SNP Chromosome Position: 132083026SNP in Genomic Sequence: SEQ ID NO: 11 SNP Position Genomic: 36804Related Interrogated SNP: hCV16176374 (Power = .6) SNP Source:dbSNP; HGBASE Population (Allele, Count): Caucasian (G, 85|A, 35)SNP Type: INTRON Context (SEQ ID NO: 54):ATTTATATGACATTTCAAGAAAAGGCAAAATTATAGTGACAGAAAGCAGATCAATAGTTGCTTGGGGGTGGGTCTGCAAATGGGCATAAAGGAAATTTTG RGGATGACAAGGGTGTTCTAAAGCTGGATTGTGATGATGGTTTCACAACTGTATATATTTACTACACTCATCAAACTGCACAGCTGCAATATGTGAATTTA Celera SNP ID: hCV30117349Public SNP ID: rs9784675 SNP Chromosome Position: 132097638SNP in Genomic Sequence: SEQ ID NO: 11 SNP Position Genomic: 51416Related Interrogated SNP: hCV16176374 (Power = .51) SNP Source:dbSNP; HapMap; ABI_Val Population (Allele, Count):Caucasian (A, 99|G, 21) SNP Type: INTRON Gene Number 3 Gene Symbol:IL4 - 3565 Gene Name: interleukin 4 Chromosome: 5 OMIM NUMBER: 147780OMIM Information: Genomic Sequence (SEQ ID NO: 12): SNP InformationContext (SEQ ID NO: 55):TATTCTAAATACTTGAAAACTTTAAATGTATTCATTCCTCAGAGCAACTTCATGAGACAGGGACAGCTATGACCCCTATTTCACAGATGAGGCTGAGTAG MGTGCCCAAGGTCACACAGCCAGGAGGCACAGCAGCCAGGCCTGACAGACCACCTGGGCCCAGCGTCCGCTCTCTTAGCCACCGTGTACTATAGCAGCCTC Celera SNP ID: hCV2259917Public SNP ID: rs762534 SNP Chromosome Position: 132032655SNP in Genomic Sequence: SEQ ID NO: 12 SNP Position Genomic: 5383SNP Source: dbSNP; Celera; HapMap; ABI_Val; HGBASEPopulation (Allele, Count): Caucasian (C, 111|A, 9) SNP Type:INTERGENIC; UNKNOWN Context (SEQ ID NO: 56):CACAGCAGGGAGAGTGCTGTGTTATGCGAGGAGGTTGGAGAAATCCTCCCCATGAGATAAGATGGGAACAGAGATCGGGACGAAACAAGGGGAGGGGACA MCCATGCACAGATCGGGGCAAAGTCATCAAGGGAAAGGGAACTGCAGGTGCTAAGGTCTTGAGCAAGAGCGAGCTGGGGATGCCCTTCCCAGCACTCACGG Celera SNP ID: hCV16176063Public SNP ID: rs2243211 SNP Chromosome Position: 132029321SNP in Genomic Sequence: SEQ ID NO: 12 SNP Position Genomic: 2049SNP Source: dbSNP; HapMap; HGBASE Population (Allele, Count):Caucasian (C, 108|A, 12) SNP Type: TFBS SYNONYMOUS; INTERGENIC; UNKNOWNContext (SEQ ID NO: 57):GGCAGACACACTCAGCAGCCAGAGCTAGACAGGCAGGTGGTAGGAGTCCAGGGCCACGGCAGGGATGGAGTGTCGCCCCCTCGCTGCGATACCAGAGCAA STAAAACGTTAAGGCCTTGCACTAAAGCTGCCCTTAGGATGCATTCTTTTAAAGTTTTTCCATTTAATGCAGACTCTTTTCAATTCTTATTTTATCCTTGT Celera SNP ID: hCV16176374Public SNP ID: rs2227282 SNP Chromosome Position: 132041078SNP in Genomic Sequence: SEQ ID NO: 12 SNP Position Genomic: 13806SNP Source: dbSNP; HapMap; HGBASE Population (Allele, Count):Caucasian (G, 32|C, 86) SNP Type: INTRON Context (SEQ ID NO: 58):GGGTGTCTATGAAGTCAAGGCTGTCTGAGGAACAGCAAAGTGGGAAGAAGCAAGCTGGCTGGCTGATGAAGGGTTTCTTGGGTGGACAAGTAGTTGGAGC KATTTCCTATTTACCAAAGAGAGCTAAAGTTCATAATTCTACAGAGAGTTCCATAATGAACCTCAAATACCTCTGTTTTTTGAAGGAGTTTCTCATATACA Celera SNP ID: hCV11818513Public SNP ID: rs2227284 SNP Chromosome Position: 132040624SNP in Genomic Seauence: SEQ ID NO: 12 SNP Position Genomic: 13352Related Interrogated SNP: hCV16176374 (Power = .7) SNP Source:dbSNP; Celera; HapMap; HGBASE Population (Allele, Count):Caucasian (T, 32|G, 86) SNP Type: INTRON Context (SEQ ID NO: 59):GGCCAGGATGGTCTCAATCTCTTGACCTCGTGATCCACCTGCCTCAACCTCCCAAAGTGCTGGGATTACAGGGGTGAGCCACCACACCCGGCCCAGCAGT WGTTTTTCTAAAACACAAATAGGCCAGGTGCAGTGGCTCACGCCTGTAATCCCGGCACTTTGGGAGACTGAGATGGGAGCTTCGCTTGAACCCAAAAGTTC Celera SNP ID: hCV15793498Public SNP ID: rs2406539 SNP Chromosome Position: 132051175SNP in Genomic Sequence: SEQ ID NO: 12 SNP Position Genomic: 23903Related Interrogated SNP: hCV16176374 (Power = .7) SNP Source:dbSNP; HapMap; HGBASE Population (Allele, Count):Caucasian (A, 29|T, 77) SNP Type:TRANSCRIPTION FACTOR BINDING SITE; INTERGENIC; UNKNOWNContext (SEQ ID NO: 60):TCTTCCTAGTCCAACTTTAAGTCTCTAAGCTGTCTGTTCCTTCTAGTTTCTGATTAGCCAGAGTTCAGCCAAACGAAAATATGTTTTGATGTTTTGTATG STCACTGCACACCTGGGTACTTACTAGGCAACGTGAATAAGAGGACACACATTTGCTCCCTCAGTTTATACCAATCACGAGTGCAAGCAAAACAGCTGAGA Celera SNP ID: hCV26478954Public SNP ID: rs4426908 SNP Chromosome Position: 132050617SNP in Genomic Sequence: SEQ ID NO: 12 SNP Position Genomic: 23345Related Interrogated SNP: hCV16176374 (Power = .7) SNP Source:dbSNP; Celera; HGBASE Population (Allele, Count):Caucasian (C, 32|G, 88) SNP Type:TRANSCRIPTION FACTOR BINDING SITE; INTERGENIC; UNKNOWNContext (SEQ ID NO: 61):TCTAAAAAGGGATGGGGGAGGGGAGCAGGTGGAGAGGAATATCTGATCTGTCATATTCTTTAGTCAGAGCCATAAACGTGTTTGGGTGAGACAATCTGAT STTCTGATAACGTTGATAAAAGTCACTTGAAGATTGGGTCACAGGAAGCCCAAGATAAATGCTGAGAGGAAACAGGTTCTTTTTGAAGTAGCCTCTTCGTA Celera SNP ID: hCV31237737Public SNP ID: rs11242122 SNP Chromosome Position: 132052607SNP in Genomic Sequence: SEQ ID NO: 12 SNP Position Genomic: 25335Related Interrogated SNP: hCV16176374 (Power = .7) SNP Source:dbSNP; HapMap; ABI_Val Population (Allele, Count):Caucasian (C, 31|G, 89) SNP Type: INTERGENIC; UNKNOWNContext (SEQ ID NO: 62):TACACTTAAAACAGGGCACATGCTGGGCACAGTGGCTCACGCCTGTAACCTCAGCACTTTGGGAGCCCAAGGCGGGAGGACTGCTTGAAGCCAGGAGTTC YAAACCAACCTGGGCAACTTAGCAAGCTCCTATCTCTACAAAAAATTAAAAAATTAGCCAAGTGTAGTGGCAGACACCTGTGGTCCCAGCTACTTGGGAGG Celera SNP ID: hCV31237741Public SNP ID: rs11747814 SNP Chromosome Position: 132052065SNP in Genomic Sequence: SEQ ID NO: 12 SNP Position Genomic: 24793Related Interrogated SNP: hCV16176374 (Power = .7) SNP Source:dbSNP; HapMap Population (Allele, Count): Caucasian (C, 31|T, 89)SNP Type: INTERGENIC; UNKNOWN Gene Number: 4 Gene Symbol: IL5 - 3567Gene Name: interleukin 5 (colony-stimulating factor, eosinophil)Chromosome: 5 OMIM NUMBER: 147850 OMIM Information:Genomic Sequence (SEQ ID NO: 13): SNP InformationContext (SEQ ID NO: 63):TCTGCCACAGGCAGATCCGGGTGATGGTCAGCTTGGCTGTGTGAATGGGACTCAGTGGAAAGGACTGCCTTCTGTGGGGTGCAGAACAGGGGCATTACTT KTTGAATGTCCTGATGAGCCACACACAGATCTAACCATGCTGTATCAGGAGAGAGTCAGTGCTAGTCATGCACAGTCATGCACAAGGGAACTTGCAAACAC Celera SNP ID: hCV28028637Public SNP ID: rs4143832 SNP Chromosome Position: 131890876SNP in Genomic Sequence: SEQ ID NO: 13 SNP Position Genomic: 20000SNP Source: dbSNP; HapMap; HGBASE Population (Allele, Count):Caucasian (T, 17|G, 103) SNP Type: INTRON Context (SEQ ID NO: 64):AGTTCAGCTACAGAGACGGAGGCAATGTGAACTACCATTTAGATTTTTTAAAATCCACGTTATTTTAGGGAAATAGAAAGAAATAAACAATTAGTACTTT SATTTTTAAATAATTACTGGTTGGTAATTTTATAATTTAAAAAAAGCACTTTGATTAATATTGAAAAGTTACATTGGTGGGTAACATCCATCCTTTTGCCC Celera SNP ID: hCV11818554Public SNP ID: rs12652920 SNP Chromosome Position: 131913139SNP in Genomic Sequence: SEQ ID NO: 13 SNP Position Genomic: 42263Related Interrogated SNP: hCV50000065 (Power = .51) SNP Source:dbSNP; Celera; HapMap; ABI_Val Population (Allele, Count):Caucasian (G, 93|C, 25) SNP Type: TFBS SYNONYMOUS; INTRON Gene Number: 5Gene Symbol: LOC44110 - 441108 Gene Name:hypothetical gene supported by AK128882 Chromosome: 5 OMIM NUMBER:OMIM Information: Genomic Sequence (SEQ ID NO: 14): SNP InformationContext (SEQ ID NO: 65):TCTGCCACAGGCAGATCCGGGTGATGGTCAGCTTGGCTGTGTGAATGGGACTCAGTGGAAAGGACTGCCTTCTGTGGGGTGCAGAACAGGGGCATTACTT KTTGAATGTCCTGATGAGCCACACACAGATCTAACCATGCTGTATCAGGAGAGAGTCAGTGCTAGTCATGCACAGTCATGCACAAGGGAACTTGCAAACAC Celera SNP ID: hCV28028637Public SNP ID: rs4143832 SNP Chromosome Position: 131890876SNP in Genomic Sequence: SEQ ID NO: 14 SNP Position Genomic: 126304SNP Source: dbSNP; HapMap; HGBASE Population (Allele, Count):Caucasian (T, 17|G, 103) SNP Type: INTRON Context (SEQ ID NO: 66):ATCTGACTTCCCCCTAGCCGACTTAACCCTCAGGTGGGCCCCCTTCTCATCATTATCAGGCTCTGAATCCCCACACTATTCCCTGGCGTGGACACTCTGC KTCTGAGCTGGATCCCCCCTATTTGTGGATTCCTCTTTCATCCTGCTGGAACTCTGATACCATTGGACTCTTGAAACTCTGTCTATGCCAAGCTGTTTCCC Celera SNP ID: hCV2549985Public SNP ID: rs2299015 SNP Chromosome Position: 131929396SNP in Genomic Sequence: SEQ ID NO: 14 SNP Position Genomic: 164824Related Interrogated SNP: hCV50000065 (Power = .51) SNP Source:dbSNP; Celera; HapMap; HGBASE Population (Allele, Count):Caucasian (T, 89|G, 21) SNP Type: INTRON Context (SEQ ID NO: 67):CATTAACAGAATAAAAAAGAAATATCATATGAACACCAATAGATACAGAAAACGCATTTCAATTTAATAGTCTTTCGTGGTAAAAACCCTCAGCATAACT RATGGAGGAATATTAATTCCTGAATAATTCAGTCCAAAATCCGTTAGGTGTGGCTGAGTGAGGAAGGCATCCACAAAAACAAGCTGTGACAGCCTGGTGGG Celera SNP ID: hCV11818538Public SNP ID: rs2706348 SNP Chromosome Position: 131933709SNP in Genomic Sequence: SEQ ID NO: 14 SNP Position Genomic: 169137Related Interrogated SNP: hCV50000065 (Power = .51) SNP Source:dbSNP; Celera; HapMap; ABI_Val; HGBASE Population (Allele, Count):Caucasian (G, 94|A, 26) SNP Type: INTRON Context (SEQ ID NO: 68):AGTTCAGCTACAGAGACGGAGGCAATGTGAACTACCATTTAGATTTTTTAAAATCCACGTTATTTTAGGGAAATAGAAAGAAATAAACAATTAGTACTTT SATTTTTAAATAATTACTGGTTGGTAATTTTATAATTTAAAAAAAGCACTTTGATTAATATTGAAAAGTTACATTGGTGGGTAACATCCATCCTTTTGCCC Celera SNP ID: hCV11818554Public SNP ID: rs12652920 SNP Chromosome Position: 131913139SNP in Genomic Sequence: SEQ ID NO: 14 SNP Position Genomic: 148567Related Interrogated SNP: hCV50000065 (Power = .51) SNP Source:dbSNP; Celera; HapMap; ABI_Val Population (Allele, Count):Caucasian (G, 93|C, 25) SNP Type: TFBS SYNONYMOUS; INTRONContext (SEQ ID NO: 69):AAAATATACTGTGCCAGCTAATGAAAAGAAAGCTGAAGTGACCATATTAATACCAGACAGAAGACATCAGAACTAGGGAAAATGAAACATTTTATGATGA KAAGAGGTCAATTTAATGCAAGGACACAAAAATTCTAAATGTAAAACTTCCAAATATATGAGGCAGAAACCTATGGAACAGAATGGAGAAATACACAAATC Celera SNP ID: hCV16274080Public SNP ID: rs2706347 SNP Chromosome Position: 131933016SNP in Genomic Sequence: SEQ ID NO: 14 SNP Position Genomic: 168444Related Interrogated SNP: hCV50000065 (Power = .51) SNP Source:dbSNP; HGBASE Population (Allele, Count): Caucasian (G, 92|T, 26)SNP Type: TRANSCRIPTION FACTOR BINDING SITE; INTRONContext (SEQ ID NO: 70):GTATGCCAGTCTTCCTTATCCTGCGTAGGCTCTTGACTCTTCATTCTGACTCCCTCATGGGATGCTTTTCCATTCTGTATACACTTTGACTTCTGGTGCT RGATCATGTCCTCATTCCCCGCCCTTCTCTGATACCAGGTGGCCTCTTGCAGGGATGCCCACTGTACTCTGACCTGAATCTCCCCAGATCTGTGTCACTGA Celera SNP ID: hCV16274083Public SNP ID: rs2244012 SNP Chromosome Position: 131929124SNP in Genomic Sequence: SEQ ID NO: 14 SNP Position Genomic: 164552Related Interrogated SNP: hCV50000065 (Power = .51) SNP Source:dbSNP; HapMap; ABI_Val; HGBASE Population (Allele, Count):Caucasian (A, 94|G, 26) SNP Type: INTRON Context (SEQ ID NO: 71):CACACACACACACACACACACATATATATATAGTTTATTCGTTTTTAGTGGGGTCATGTGCCTCTCTAGCCGCTCCCTGACCCCAGTTCCACTATGTTTT YGTTACGTATTCTTCCAAGCTTTTTTCTGCTTATAAAACCATGTCTACGTGAGCACATAAATGCATTCACACATACATATTTTAGCACATTAATATAATTT Celera SNP ID: hCV16274086Public SNP ID: rs2706338 SNP Chromosome Position: 131923748SNP in Genomic Sequence: SEQ ID NO: 14 SNP Position Genomic: 159176Related Interrogated SNP: hCV50000065 (Power = .51) SNP Source:dbSNP; HapMap; ABI_Val; HGBASE Population (Allele, Count):Caucasian (C, 94|T, 26) SNP Type: INTRON Gene Number: 6 Gene Symbol:P4HA2 - 8974 Gene Name:procollagen-proline, 2-oxoglutarate 4-dioxygenase (proline 4-hydroxylase),alpha polypeptide II Chromosome: 5 OMIM NUMBER: 600608 OMIM Information:Genomic Sequence (SEQ ID NO: 15): SNP InformationContext (SEQ ID NO: 72):TCCTACACACAGCTACTTCTCAGGGACTGCTGGTCCTAGAGCCTTAGGTGGGGCCTTTTCCAACACTGTGTGCACTTCAAGCCCAGATCCGCCATTTTCT STTCATCTTCCCTGGGATGAGACAGCTTCTTGTTTAACTCTCCACACATAGAAGTTCTCATTATACATTCTCTTAGAGCTCCTGGTTTCTCCTGCAGGAGA Celera SNP ID: hCV559494Public SNP ID: rs334902 SNP Chromosome Position: 131614458SNP in Genomic Sequence: SEQ ID NO: 15 SNP Position Genomic: 68256SNP Source: dbSNP; Celera; HapMap; HGBASE Population (Allele, Count):Caucasian (G, 44|C, 70) SNP Type: MICRORNA; UTR3; INTRONContext (SEQ ID NO: 73):GAGCACTCACAGCCGGGCTCCTCCCCTGGCACATGGCCAGCTGCCAATATGAAGCAGCAATCTCAGAGTACGAGCTACCCACAGGCAAGAATAGTGCCTC SGCCACCTCCTCTCTCTCGTCCCTCATTCTAGCCCCAGGCACGCTCCAGTCAGAAGCCAAACAGGCAGAAGGCACTCAAGGGATGAACTGAGATCAGCTGG Celera SNP ID: hCV2346958Public SNP ID: rs157578 SNP Chromosome Position: 131589221SNP in Genomic Sequence: SEQ ID NO: 15 SNP Position Genomic: 43019SNP Source: dbSNP; HapMap; ABI_Val; HGBASE Population (Allele, Count):Caucasian (G, 110|C, 8) SNP Type: INTRON Context (SEQ ID NO: 74):AGCCTTAGGTGGGGCCTTTTCCAACACTGTGTGCACTTCAAGCCCAGATCCGCCATTTTCTCTTCATCTTCCCTGGGATGAGACAGCTTCTTGTTTAACT MTCCACACATAGAAGTTCTCATTATACATTCTCTTAGAGCTCCTGGTTTCTCCTGCAGGAGAGGCACAGACTCCGTTGTTCCTAAGCAAGCCTATCTTCCC Celera SNP ID: hCV26479272Public SNP ID: rs4594848 SNP Chromosome Position: 131614497SNP in Genomic Sequence: SEQ ID NO: 15 SNP Position Genomic: 68295SNP Source: dbSNP; Celera; HapMap; HGBASE Population (Allele, Count):Caucasian (C, 62|A, 58) SNP Type: MICRORNA; UTR3; INTRONContext (SEQ ID NO: 75):CCTAGTACCTCAAGCCAAAGCTGTTCCAAGATGAGGTCCAGGGGCCAGGATAGGAACCTATTTCAGGTCTCTCCATGAGTGTCGGGCCTCCTGGTCACCT YGGCCCCTACAATTCTATTAGGAGCAGAGCAATAGAGAATCGAGCTAAATCCTCCCTCCCAATCATCAGTGATGGGATATGGCAGCAAATAGGTCTCTTTG Celera SNP ID: hDV70977429Public SNP ID: rs17618604 SNP Chromosome Position: 131570083SNP in Genomic Sequence: SEQ ID NO: 15 SNP Position Genomic: 23881SNP Source: dbSNP; HapMap Population (Allele, Count):Caucasian (C, 104|T, 14) SNP Type: INTRON Gene Number: 7 Gene Symbol:RAD50 - 10111 Gene Name: RAD50 homolog (S. cerevisiae) Chromosome: 5OMIM NUMBER: 604040 OMIM Information: Genomic Sequence (SEQ ID NO: 16):SNP Information Context (SEQ ID NO: 76):TTACAATTAGATTCCTGGGAAGCACAAACATTTAAAATGTTAGCAGGCAAAGGAAAAGGAGCAAGTGAAGGAAACTGGGATGTGCCCAGGGAACCAGGGT KAGAGCCAGATAGCTGTGGTGTCTAGGTGCCTTGGGAAAATAGTCTTCAAGGAGAAGGTCAACAGTGTTTGGTGCTACGTAGAGGTAGAGTAAGATGAAGA Celera SNP ID: hCV16154343Public SNP ID: rs2897443 SNP Chromosome Position: 131957493SNP in Genomic Sequence: SEQ ID NO: 16 SNP Position Genomic: 46964SNP Source: dbSNP; Celera; HapMap; ABI_Val; HGBASEPopulation (Allele, Count): Caucasian (G, 94|T, 26) SNP Type: INTRONContext (SEQ ID NO: 77):ACCACAGTAATAATTATTGCAAGCAAGATCTGTCAGTGGATACTAAAATCAGTAGGCAGAAAGTTGAGAAGCAAGATATTTACATAGTCTCAACATTTCT YTCCTAAGATACTTGTTAATTACAAAGACTAAAACAGTAACTTTACAGTGGAGAAACCTGGCCAACACCATCTAAGCCAAGTGAATAAGGATTAACATCAT Celera SNP ID: hCV29134417Public SNP ID: rs6884762 SNP Chromosome Position: 131966629SNP in Genomic Sequence: SEQ ID NO: 16 SNP Position Genomic: 56100SNP Source: dbSNP; HapMap Population (Allele, Count):Caucasian (C, 112|T, 6) SNP Type: INTRON Context (SEQ ID NO: 78):TTTTAAAAGAATTTTAGCCTCAGCCTGGTATCCTTTGAGAGTTACTAGAAGGTGAACAGTGTTTTGATACAATTATATTTCATGGCCTTAAGAACTTTAT YACTGAAGAAGTGATATAGAATTGGTAATCACACTGTAGTGATGGGCCTTAGTTATTCAGTATTGAACATGCTTAGCCCCCATACATCTGCTAGCCTGCTG Celera SNP ID: hCV15756644Public SNP ID: rs2301713 SNP Chromosome Position: 131979895SNP in Genomic Sequence: SEQ ID NO: 16 SNP Position Genomic: 69366Related Interrogated SNP: hCV50000065 (Power = .51) SNP Source:dbSNP; HapMap; ABI_Val; HGBASE Population (Allele, Count):Caucasian (T, 91|C, 25) SNP Type: INTRON Context (SEQ ID NO: 79):GGCTGAGGAACTGGGGCATCTGGGTTGCTTCTGGCCAGACCACCAGGCTCTTGAATCCTCCCAGCCAGAGAAAGAGTTTCCACACCAGCCATTGTTTTCC YCTGGTAATGTCAGCCTCATCTGTTGTTCCTAGGCTTACTTGATATGTTTGTAAATGACAAAAGGCTACAGAGCATAGGTTCCTCTAAAATATTCTTCTTC Celera SNP ID: hCV16164126Public SNP ID: rs2074369 SNP Chromosome Position: 132001562SNP in Genomic Sequence: SEQ ID NO: 16 SNP Position Genomic: 91033Related Interrogated SNP: hCV50000065 (Power = .51) SNP Source:dbSNP; HapMap; HGBASE Population (Allele, Count):Caucasian (T, 91|C, 25) SNP Type: INTRON Context (SEQ ID NO: 80):AAGAGCGTGAACTCTGGAGCTGGACTGGGTTAAAATCTTGGCTGCTTCATTTACTGGCTGTTGTGACCCTGGACAAATCATTCTCTGTGTCTGTTTGCTC RTTTGAAATATAGGACTGAAAATGATGGTACTGTCCTCATAGGGTCATTGAAAGGAGCAAATGAGTTGACTTTTAGAGCCTGGCACATAGAAAGTGCTTTT Celera SNP ID: hCV25471631Public SNP ID: rs2522394 SNP Chromosome Position: 131972028SNP in Genomic Sequence: SEQ ID NO: 16 SNP Position Genomic: 61499Related Interrogated SNP: hCV50000065 (Power = .51) SNP Source: AppleraPopulation (Allele, Count):Caucasian (A, 6|G, 34) African American (A, 26|G, 12) total (A, 32|G, 46)SNP Type: INTRON SNP Source: dbSNP; HapMap; ABI_Val; HGBASEPopulation (Allele, Count): Caucasian (G, 94|A, 26) SNP Type: INTRONContext (SEQ ID NO: 81):GTTCAAGACTCTTCTGAGCAGTGATACCAGCAATTTAGTTCAGTCCTAAAGAACTGAGGGTCCTGGGAATTTAACCATGTCAGTGTAGTCTTTTTTACAT YGCTAGCATAAAAATGGGTGCCCTTTAAAGATTTTTTTAAGATTAAGAAACTAGAAGACAGGAGGAGCCAAATCAGGACTGTAAGGTGGATGCCTAATGAT Celera SNP ID: hCV2549970Public SNP ID: rs10463893 SNP Chromosome Position: 131955938SNP in Genomic Sequence: SEQ ID NO: 16 SNP Position Genomic: 45409Related Interrogated SNP: hCV50000065 (Power = .51) SNP Source:dbSNP; Celera; HapMap Population (Allele, Count):Caucasian (T, 93|C, 25) SNP Type: INTRON Context (SEQ ID NO: 82):AATGGAAGTAAGTCGCCTCACATCCTCACATCCTTTGTATGATGATCGCAGTAATGTTTGCCTTTTTACCACTGGTGCAACATTTATTAGTTCATAAACC YGCTTCCAAAGAACCTAAGGGCTTTTTGATGAAAGGTGACTGTGGTGGGAACAATGTTAGGTTTTGACAGGCTACTTTTGCTTTTACAAACATTTCTCCTC Celera SNP ID: hCV2549979Public SNP ID: rs12653750 SNP Chromosome Position: 131999801SNP in Genomic Sequence: SEQ ID NO: 16 SNP Position Genomic: 89272Related Interrogated SNP: hCV50000065 (Power = .51) SNP Source:dbSNP; Celera; HapMap Population (Allele, Count):Caucasian (C, 94|T, 26) SNP Type: INTRON Context (SEQ ID NO: 83):GTAAAATAAAATTTTGATGTCAGTTCAGCTTAAGCTTCTAAATCATTCTCGCTGAACCAAAGCTTCCAGTTGGTAAAAATCTAAGATCTGAGGAATAAAA SCAACATAAGAAGCTGACTTTTGGTAAGCCTTAACAGTGATAGAAGAGGGACAAGGTGGCAGTTCGATTCTCCTATTTTCCCCATAGACTGCAGGCCCCTT Celera SNP ID: hCV2549980Public SNP ID: rs2040703 SNP Chromosome Position: 132000157SNP in Genomic Sequence: SEQ ID NO: 16 SNP Position Genomic: 89628Related Interrogated SNP: hCV50000065 (Power = .51) SNP Source:dbSNP; Celera; HapMap; HGBASE Population (Allele, Count):Caucasian (C, 92|G, 26) SNP Type: INTRON Context (SEQ ID NO: 84):CAAGGTTGTCAAGCAGCTCTTGCATAAGGACTATGCTGGCAGAGAAAAAGGCAGTTTCCCTGAGGTCAAAGGAGGTGTTTCAGGCACTCCTGGCTCCAGA YAGTCCCTTTCTGGCAGAGAGGGCCAGAAGGAGAGCTCAGCAGCGCAGGGCCACCTTTCTGCAGCCATCATCACAAGTAAGGGCGAGTGCTTTTGAAACCT Celera SNP ID: hCV2549981Public SNP ID: rs2240032 SNP Chromosome Position: 132005026SNP in Genomic Sequence: SEQ ID NO: 16 SNP Position Genomic: 94497Related Interrogated SNP: hCV50000065 (Power = .51) SNP Source:dbSNP; Celera; HapMap; ABI_Val; HGBASE Population (Allele, Count):Caucasian (C, 92|T, 24) SNP Type: INTRON Context (SEQ ID NO: 85):ATCTGACTTCCCCCTAGCCGACTTAACCCTCAGGTGGGCCCCCTTCTCATCATTATCAGGCTCTGAATCCCCACACTATTCCCTGGCGTGGACACTCTGC KTCTGAGCTGGATCCCCCCTATTTGTGGATTCCTCTTTCATCCTGCTGGAACTCTGATACCATTGGACTCTTGAAACTCTGTCTATGCCAAGCTGTTTCCC Celera SNP ID: hCV2549985Public SNP ID: rs2299015 SNP Chromosome Position: 131929396SNP in Genomic Sequence: SEQ ID NO: 16 SNP Position Genomic: 18867Related Interrogated SNP: hCV50000065 (Power = .51) SNP Source:dbSNP; Celera; HapMap; HGBASE Population (Allele, Count):Caucasian (T, 89|G, 21) SNP Type: INTRON Context (SEQ ID NO: 86):GAGCCTAACAGGACTTACATATTTGACTGCAGTAGGCATTATATTTAGCTGATGACATAATAGGTTCTGTCATAGTGTAGATAGGGATAAGCCAAAATGC RATAAGAAAAACCATCCAGAGGAAACTCTTTTTTTTTTCTTTTTCTTTTTTTTTTTTCCAGATGGAGTCTCGCACTTCTCTGTCACCCGGGCTGGAGCGCA Celera SNP ID: hCV11740472Public SNP ID: rs2040704 SNP Chromosome Position: 132001076SNP in Genomic Sequence: SEQ ID NO: 16 SNP Position Genomic: 90547Related Interrogated SNP: hCV50000065 (Power = .51) SNP Source:dbSNP; Celera; HapMap; HGBASE Population (Allele, Count):Caucasian (A, 94|G, 26) SNP Type:TRANSCRIPTION FACTOR BINDING SITE; INTRON Context (SEQ ID NO: 87):CATTAACAGAATAAAAAAGAAATATCATATGAACACCAATAGATACAGAAAACGCATTTCAATTTAATAGTCTTTCGTGGTAAAAACCCTCAGCATAACT RATGGAGGAATATTAATTCCTGAATAATTCAGTCCAAAATCCGTTAGGTGTGGCTGAGTGAGGAAGGCATCCACAAAAACAAGCTGTGACAGCCTGGTGGG Celera SNP ID: hCV11818538Public SNP ID: rs2706348 SNP Chromosome Position: 131933709SNP in Genomic Sequence: SEQ ID NO: 16 SNP Position Genomic: 23180Related Interrogated SNP: hCV50000065 (Power = .51) SNP Source:dbSNP; Celera; HapMap; ABI_Val; HGBASE Population (Allele, Count):Caucasian (G, 94|A, 26) SNP Type: INTRON Context (SEQ ID NO: 88):AGTTCAGCTACAGAGACGGAGGCAATGTGAACTACCATTTAGATTTTTTAAAATCCACGTTATTTTAGGGAAATAGAAAGAAATAAACAATTAGTACTTT SATTTTTAAATAATTACTGGTTGGTAATTTTATAATTTAAAAAAAGCACTTTGATTAATATTGAAAAGTTACATTGGTGGGTAACATCCATCCTTTTGCCC Celera SNP ID: hCV11818554Public SNP ID: rs12652920 SNP Chromosome Position: 131913139SNP in Genomic Sequence: SEQ ID NO: 16 SNP Position Genomic: 2610Related Interrogated SNP: hCV50000065 (Power = .51) SNP Source:dbSNP; Celera; HapMap; ABI_Val Population (Allele, Count):Caucasian (G, 93|C, 25) SNP Type: TFBS SYNONYMOUS; INTRONContext (SEQ ID NO: 89):AAATGGGAATTGCTAGAGGAATATGTTTCTAACTTTTTTTTTCTGCACACAAGTTCATGGTCCTTCTATACTTGATAGCCCAGCTGCTCTATTTTTTTTA KCTCATTTCACACTGGCACCTAAGCTTTAAACCCTTGGCTGTTTTTGTTATTGTTGTCTGCCTGCTTGTCCTAGCTCCTTTTACTAGGTGTGTACTCTGGG Celera SNP ID: hCV15793510Public SNP ID: rs2252775 SNP Chromosome Position: 131946343SNP in Genomic Sequence: SEQ ID NO: 16 SNP Position Genomic: 35814Related Interrogated SNP: hCV50000065 (Power = .51) SNP Source:dbSNP; HapMap; HGBASE Population (Allele, Count):Caucasian (T, 94|G, 26) SNP Type: INTRON Context (SEQ ID NO: 90):AACTTTTTTTAACTGCATATATACAATACATATGTATATACAAACATTCACTTGTATGTATGTGCATATTTACCTTTACAAGCTTAATCAGAACAGGATT RTGAGAGGAAGAGTCTGGGTTAAGTAAATCAATATAAAAGGAGTAAATGACCAATATGAATCGGGGTCAGATTATAGAAAGCTAATGGATTTCAGACTTAG Celera SNP ID: hCV15892310Public SNP ID: rs2246176 SNP Chromosome Position: 131945249SNP in Genomic Sequence: SEQ ID NO: 16 SNP Position Genomic: 34720Related Interrogated SNP: hCV50000065 (Power = .51) SNP Source:dbSNP; HapMap; ABI_Val; HGBASE Population (Allele, Count):Caucasian (A, 93|G, 25) SNP Type: INTRON Context (SEQ ID NO: 91):TTGTAGTCCATTAAGTTATTGAACTGTGTTTGCAATTTGGATGCTTCTTTTTAACAGAAAAAATTTAAAAAGCAGAAAGGTCATCAGTTACTACCTCTCA YCCAGCAGCAACCATTGGGCATATTTTCTTTCACTTGTCTTTCTGTGCGTATATTTATTTACCTGATTGACAGTATAAATGTAATTTTTTTCACTTACCAT Celera SNP ID: hCV15892315Public SNP ID: rs2522403 SNP Chromosome Position: 131943216SNP in Genomic Sequence: SEQ ID NO: 16 SNP Position Genomic: 32687Related Interrogated SNP: hCV50000065 (Power = .51) SNP Source:dbSNP; HapMap; HGBASE Population (Allele, Count):Caucasian (T, 94|C, 26) SNP Type: INTRON Context (SEQ ID NO: 92):TTGGTACATAACAGTACTTTTTACATTCATTCACATTACTAAGTACAACTATTTTTCAAACGTTTCTTCAACCAGGACATAACAGAAATGCCAACAAGAC WTGTAATCCAGTCGACTCTGTAAGGATGCCCATAAGCTTGAGAGTAGTGCCTGACACATAAGAGGATGCTTAATAAGTGATAATAAATAAATGAAGATTTT Celera SNP ID: hCV16098376Public SNP ID: rs2106984 SNP Chromosome Position: 131980965SNP in Genomic Sequence: SEQ ID NO: 16 SNP Position Genomic: 70436Related Interrogated SNP: hCV50000065 (Power = .51) SNP Source:dbSNP; Celera; HapMap; HGBASE Population (Allele, Count):Caucasian (T, 94|A, 26) SNP Type: INTRON Context (SEQ ID NO: 93):AAAATATACTGTGCCAGCTAATGAAAAGAAAGCTGAAGTGACCATATTAATACCAGACAGAAGACATCAGAACTAGGGAAAATGAAACATTTTATGATGA KAAGAGGTCAATTTAATGCAAGGACACAAAAATTCTAAATGTAAAACTTCCAAATATATGAGGCAGAAACCTATGGAACAGAATGGAGAAATACACAAATC Celera SNP ID: hCV16274080Public SNP ID: rs2706347 SNP Chromosome Position: 131933016SNP in Genomic Sequence: SEQ ID NO: 16 SNP Position Genomic: 22487Related Interrogated SNP: hCV50000065 (Power = .51) SNP Source:dbSNP; HGBASE Population (Allele, Count): Caucasian (G, 92|T, 26)SNP Type: TRANSCRIPTION FACTOR BINDING SITE; INTRONContext (SEQ ID NO: 94):GTATGCCAGTCTTCCTTATCCTGCGTAGGCTCTTGACTCTTCATTCTGACTCCCTCATGGGATGCTTTTCCATTCTGTATACACTTTGACTTCTGGTGCT RGATCATGTCCTCATTCCCCGCCCTTCTCTGATACCAGGTGGCCTCTTGCAGGGATGCCCACTGTACTCTGACCTGAATCTCCCCAGATCTGTGTCACTGA Celera SNP ID: hCV16274083Public SNP ID: rs2244012 SNP Chromosome Position: 131929124SNP in Genomic Sequence: SEQ ID NO: 16 SNP Position Genomic: 18595Related Interrogated SNP: hCV50000065 (Power = .51) SNP Source:dbSNP; HapMap; ABI_Val; HGBASE Population (Allele, Count):Caucasian (A, 94|G, 26) SNP Type: INTRON Context (SEQ ID NO: 95):CACACACACACACACACACACATATATATATAGTTTATTCGTTTTTAGTGGGGTCATGTGCCTCTCTAGCCGCTCCCTGACCCCAGTTCCACTATGTTTT YGTTACGTATTCTTCCAAGCTTTTTTCTGCTTATAAAACCATGTCTACGTGAGCACATAAATGCATTCACACATACATATTTTAGCACATTAATATAATTT Celera SNP ID: hCV16274086Public SNP ID: rs2706338 SNP Chromosome Position: 131923748SNP in Genomic Sequence: SEQ ID NO: 16 SNP Position Genomic: 13219Related Interrogated SNP: hCV50000065 (Power = .51) SNP Source:dbSNP; HapMap; ABI_Val; HGBASE Population (Allele, Count):Caucasian (C, 94|T, 26) SNP Type: INTRON Context (SEQ ID NO: 96):AGTGCTAGGATTACAGGCATAAGCCACCATGCCCAACCAAGAGGACTTTTTTTTTTTTTAAATATGGGAAAGCAATTGCCTAAGAGTGCAGTCAGGTTGA YTTCAAATTCCAACTCTGCTGGGTGACCTTAGGGATGTTACTTAACCCATTTGGGCCTTCGTATCCCCCACGTAAAGTGAGGGGATTGATTTACATGATCA Celera SNP ID: hCV16274088Public SNP ID: rs2706372 SNP Chromosome Position: 131963376SNP in Genomic Sequence: SEQ ID NO: 16 SNP Position Genomic: 52847Related Interrogated SNP: hCV50000065 (Power = .51) SNP Source:dbSNP; HapMap; HGBASE Population (Allele, Count):Caucasian (C, 94|T, 24) SNP Type: INTRON Context (SEQ ID NO: 97):GAGAAAGAAAGGCCTAAGAAGATGTGGTTTGTGGCAGCCAACTTCTAAGATGGTCCCTAGTAATCTCGGCCTCTTGGTATTTATACTCTTGTATAGTCCC MTCTCATGCTGTTGCATGATTGGTCTATATAACTGATAAAACAGGCAGAAGTGATAGCATGGCCTTTCCAACATTAGGTTATTTAAGGTACTATGGCTTCT Celera SNP ID: hCV16274090Public SNP ID: rs2706370 SNP Chromosome Position: 131960915SNP in Genomic Sequence: SEQ ID NO: 16 SNP Position Genomic: 50386Related Interrogated SNP: hCV50000065 (Power = .51) SNP Source:dbSNP; HapMap; HGBASE Population (Allele, Count):Caucasian (A, 91|C, 25) SNP Type: INTRON Context (SEQ ID NO: 98):GAGGTGTTATAGTGCCAGGGAAAAGGGGTGCAAGACTAGTGTTTGCCTCTTATTTCTTGTCTTGTTTATAAATTCTCTACATTAAAAATATAAATTCCAA RTGAAAACAATGGAATAAACACAAACTCCCACTTTATAACCAACTAAAATGACAGTAACTGAATTTTCTAAAGTTTTAAACCCACCAAAATGGGAGAAATG Celera SNP ID: hCV27452177Public SNP ID: rs3091307 SNP Chromosome Position: 132017035SNP in Genomic Sequence: SEQ ID NO: 16 SNP Position Genomic: 106506Related Interrogated SNP: hCV50000065 (Power = .51) SNP Source:dbSNP; HapMap; ABI_Val; HGBASE Population (Allele, Count):Caucasian (A, 94|G, 26) SNP Type: INTRON Context (SEQ ID NO: 99):CTCCATAGTCTGTTTTTGACCTGGGCCTGGGATAAGAAGGAAGGGCTTTTCAGCAGAGAAAAGTGCCTCAGTCACAGAGGCATGCTGAGCAGAATGAGGA YCTATGAGGGAGCTTGGTGGAGCCTGGCGGGGTGGAGAGGTACAGGAGTGCTTTCTAGCAATTTAGGCTTGTTAAGGAACAAAGCCAGGCTGTTTACTGAG Celera SNP ID: hCV27484753Public SNP ID: rs3798135 SNP Chromosome Position: 131993008SNP in Genomic Sequence: SEQ ID NO: 16 SNP Position Genomic: 82479Related Interrogated SNP: hCV50000065 (Power = .51) SNP Source:dbSNP; HapMap; HGBASE Population (Allele, Count):Caucasian (C, 94|T, 26) SNP Type: INTRON Context (SEQ ID NO: 100):GTCACAGAGGCATGCTGAGCAGAATGAGGACCTATGAGGGAGCTTGGTGGAGCCTGGCGGGGTGGAGAGGTACAGGAGTGCTTTCTAGCAATTTAGGCTT RTTAAGGAACAAAGCCAGGCTGTTTACTGAGTTCTCTTACCTGGTACTCAGATGGATTCTTCTAAATGAAAAGAGGTGATACAAATTTCCCCAAAATTGAG Celera SNP ID: hCV25812184Public SNP ID: rs3798134 SNP Chromosome Position: 131993078SNP in Genomic Sequence: SEQ ID NO: 16 SNP Position Genomic: 82549Related Interrogated SNP: hCV50000065 (Power = .51) SNP Source:dbSNP; HapMap; ABI_Val; HGBASE Population (Allele, Count):Caucasian (G, 93|A, 25) SNP Type: INTRON Context (SEQ ID NO: 101):AGAGAGAAACAAACATCAGTGCAGTGGAAGCACCCAAGGCTACACCTGAATGGTGGGAAGCTCTTTGCTGCTATATAAAATGAATCAGGCTCAGCTACTA WTATTACACTCTCCTGAAGCTAACCAACATTTCCTGCAACATTATGTAGACTTTTAAAAGAAGGGCCTGAAGCATTCTCACAGGATAGGCTAAATGTAGAA Celera SNP ID: hCV29134412Public SNP ID: rs7737470 SNP Chromosome Position: 132001962SNP in Genomic Sequence: SEQ ID NO: 16 SNP Position Genomic: 91433Related Interrogated SNP: hCV50000065 (Power = .51) SNP Source:dbSNP; HapMap Population (Allele, Count): Caucasian (T, 94|A, 26)SNP Type: INTRON; PSEUDOGENE Context (SEQ ID NO: 102):ATATGATTTAATTCGTATTGTGCCTTTGACATGAGCAAAATGATGATGAAGCCTGTTATCCATAACTTCTTAGTGTTGATAATTGTGCATTCTCAGTTCA YAATCAGAAGATTGTGAATTTGTAATATTAATCACCAGAGTGCTTTACTTAGCGTCTAAAGGCCAGGAACTTTATCAGTGATCACATGCTATGAGGGTTCT Celera SNP ID: hCV29134413Public SNP ID: rs7449456 SNP Chromosome Position: 131981326SNP in Genomic Sequence: SEQ ID NO: 16 SNP Position Genomic: 70797Related Interrogated SNP: hCV50000065 (Power = .51) SNP Source:dbSNP; HapMap Population (Allele, Count): Caucasian (C, 91|T, 23)SNP Type: INTRON Context (SEQ ID NO: 103):AGAATATGGAGCTGTGGACCTTGTCTGGGTCAGAGCTTGTACAGTCTATAATATTGTCAATGGAGTTGTTGCCAGAGTGATTTATCCACAGAGATTCATT YTAGATTTTCTCATTTGTAATTATGTGTCCACCAGAGCATTTCTTTTGAAAGATGAGCCTCATTCTTCCTTTATCTGGTCTTATTGTTACTTATTGTAGTT Celera SNP ID: hCV29134415Public SNP ID: rs6596086 SNP Chromosome Position: 131980121SNP in Genomic Sequence: SEQ ID NO: 16 SNP Position Genomic: 69592Related Interrogated SNP: hCV50000065 (Power = .51) SNP Source:dbSNP; HapMap Population (Allele, Count): Caucasian (T, 94|C, 26)SNP Type: INTRON Context (SEQ ID NO: 104):CTAATTTTTATGTTTCCATAGGTGACCAGCTGCATGCATTAACTGTCATCTGAGTTGGATGATTGGGGTTAATATTTAAGAGCTGAGGAGCCTAACAGTC RCTTATTTACGTACTGATTTAAGCCCTGCTAAATTTAGTCCACAGAATAAAATAATTTGGAAACTTAACTGCCTTTCTCAGTTTTCAGCTGAAGGAATATA Celera SNP ID: hCV30171484Public SNP ID: rs10520114 SNP Chromosome Position: 131976790SNP in Genomic Sequence: SEQ ID NO: 16 SNP Position Genomic: 66261Related Interrogated SNP: hCV50000065 (Power = .51) SNP Source:dbSNP; HapMap Population (Allele, Count): Caucasian (A, 94|G, 26)SNP Type: INTRON Context (SEQ ID NO: 105):GGATTTTGTTACTGACATTTTATTGGCTGCACAAAAAAAGCTTGCACTTTAATTTACATTTCCCTCTTTACTAGTGAAGTTAAATGTCTTTTTGTATGTT RTCTATTTGTATTTCTTCTCCAAGAATTACCTATTCATATCTCTTTGCCAGTTTTTCTACTAGGTTGTCTGTTTCTTGATTTGTCACATTTTAATAGATTC Celera SNP ID: hCV31237845Public SNP ID: rs6596087 SNP Chromosome Position: 131996508SNP in Genomic Sequence: SEQ ID NO: 16 SNP Position Genomic: 85979Related Interrogated SNP: hCV50000065 (Power = .51) SNP Source:dbSNP; HapMap Population (Allele, Count): Caucasian (G, 93|A, 25)SNP Type: INTRON Context (SEQ ID NO: 106):CTTATGGATTCTGTTAAGCATTTTTTAATTTTATTGGGGTTTCTGTTTGGATTGCATTTAATTTATGGATTATTTGAGGAGAACGGACATCTTTGTAATA YCACATCTACCATTCTGGACTCCTTAGTATGCATCTCCTGCTCAATCATTTCCTTTTATCCTATTGTAAAGTTTTACAGCTTTTTCCTCTAGCTCCTATAC Celera SNP ID: hCV30081308Public SNP ID: rs6871536 SNP Chromosome Position: 131997773SNP in Genomic Sequence: SEQ ID NO: 16 SNP Position Genomic: 87244Related Interrogated SNP: hCV50000065 (Power = .51) SNP Source:dbSNP; HapMap Population (Allele, Count): Caucasian (T, 94|C, 26)SNP Type: INTRON Context (SEQ ID NO: 107):GAGGTAGTAACTGATGACCTTTCTGCTTTTTAAATTTTTTCTGTTAAAAAGAAGCATCCAAATTGCAAACACAGTTCAATAACTTAATGGACTACAAAGT YTATTTAAGGGTTACAAACCTTGTTGCTGAAAAAATCTCATCAAACTTTTGCTTCAAAGCCTTTCCTTCACTTAAAGGCCAATTAGAATCTTCTTGATGAC Celera SNP ID: hDV70911845Public SNP ID: rs17166050 SNP Chromosome Position: 131943112SNP in Genomic Sequence: SEQ ID NO: 16 SNP Position Genomic: 32583Related Interrogated SNP: hCV50000065 (Power = .51) SNP Source:dbSNP; HapMap Population (Allele, Count): Caucasian (C, 94|T, 26)SNP Type: TRANSCRIPTION FACTOR BINDING SITE; INTRON Gene Number: 8Gene Symbol: SLC22A4 - 6583 Gene Name:solute carrier family 22 (organic cation transporter), member 4Chromosome: 5 OMIM NUMBER: 604190 OMIM Information:{Rheumatoid arthritis, susceptibility to}, 180300 (3)Genomic Sequence (SEQ ID NO: 17): SNP InformationContext (SEQ ID NO: 108):ATTAGGACATTTGAAGAGAAAATGCTATTTTGGGAATATATTTATGTTAATAAAAGTACTCCCACTGAAGCAAAAAGGACAATAAAAATAACTGATATAA RAAAGTATCACTTCTAAAAGCACCATTGTTTATACCGGGTCTCTTTTCCAGATTATTACTTCTTATCCATTGGTCTGGTCATGCTGGGAAAATTTGGGATC Celera SNP ID: hCV25603190Public SNP ID: rs41542912 SNP Chromosome Position: 131699359SNP in Genomic Sequence: SEQ ID NO: 17 SNP Position Genomic: 51315SNP Source: Applera Population (Allele, Count):Caucasian (A, 2|G, 38) African American (A, 0|G, 34) total (A, 2|G, 72)SNP Type: TRANSCRIPTION FACTOR BINDING SITE; INTRON SNP Source:dbSNP; HapMap Population (Allele, Count): Caucasian (G, 114|A, 6)SNP Type: TRANSCRIPTION FACTOR BINDING SITE; INTRON Gene Number: 9Gene Symbol: SLC22A5 - 6584 Gene Name:solute carrier family 22 (organic cation transporter), member 5Chromosome: 5 OMIM NUMBER: 603377 OMIM Information:Carnitine deficiency, systemic primary, 212140 (3)Genomic Sequence (SEQ ID NO: 18): SNP InformationContext (SEQ ID NO: 109):TTGTTTCTTATACCTAAGGTGGCTTGTCACCTTACAAAGCTAACCCCAAACGTAAAATGTAAAGCACAAATAGATTTGGAGTTAGAAGTATTTCATCTCT WGAGTATTAGCAATTATTCATTAAAAAGAAAAAAAAAGTGTTTAGTCTCTTTCTGCCCTCCAATGGTTAATTATTGCATATCATCTTGGAGTCAGGTCCTT Celera SNP ID: hCV15949533Public SNP ID: rs35306350 SNP Chromosome Position: 131751188SNP in Genomic Sequence: SEQ ID NO: 18 SNP Position Genomic: 27845SNP Source: HGBASE; dbSNP Population (Allele, Count): no_pop (A, -IT, —)SNP Type: INTRON Context (SEQ ID NO: 110):AGGGCTAATATAGTGTTTTTCAAACCTTTCTAAACATTTTGGCCACAGAACTTTCATTAAAGTAGGATAATTTAAGTCTAGTAAATGAAATACACCCTAA RTGGCTAAAAGTATGGCTGTTCTGCCTGCAGCCCCTGCCTTCAATTCCCAATGCCCTGCCTCAAGCCTGTCTGTGCCCCCTTGGAAGGCCCAGGGCCCTGT Celera SNP ID: hDV70978086Public SNP ID: rs17622208 SNP Chromosome Position: 131744949SNP in Genomic Sequence: SEQ ID NO: 18 SNP Position Genomic: 21606SNP Source: dbSNP; HapMap Population (Allele, Count):Caucasian (G, 57|A, 61) SNP Type: UTR5; INTRON

TABLE 3 Primers Primer 1 Primer 2 (Allele-specific (Allele-specificMarker Rs number Alleles Primer) Primer) Common Primer hCV15949533rs2073644 C/T TTGGAGTTAGAAGTATT GATTTGGAGTTAGAAGTA GGGGGAAGAGGTGGACATCArs35306350 TCATCTCC (SEQ ID TTTCATCTCT (SEQ ID (SEQ ID NO: 113) NO:111)NO: 112) hCV16154343 rs2897443 G/T CCACAGCTATCTGGCT CCACAGCTATCTGGCTCTAGAGTTATGCAAAGGGAAGG CTC (SEQ ID NO: 114) A (SEQ ID NO: 115)AGTTACA (SEQ ID NO: 116) hCV16176063 rs2243211 A/C CCGATCTGTGCATGGTCCGATCTGTGCATGGG CCGCTACCGTGGGAAATAGA (SEQ ID NO: 117) (SEQ ID NO: 118)AC (SEQ ID NO: 119) hCV16176374 rs2227282 C/G GCAAGGCCTTAACGTTGCAAGGCCTTAACGTTTT CTCAGCAGCCAGAGCTAGAC TTAG (SEQ ID NO: 120)AC (SEQ ID NO: 121) A (SEQ ID NO: 122) hCV2259917 rs762534 A/CCACAGATGAGGCTGAG ACAGATGAGGCTGAGTAG GGTCTGTTAACAGAGGCTGCTTAGA (SEQ ID NO: 123) C (SEQ ID NO: 124) ATAG (SEQ ID NO: 125)hCV2259921 rs20541 A/G CTTTCGAAGTTTCAGTT TTCGAAGTTTCAGTTGAAGTTTTCCAGCTTGCATGTC GAACT (SEQ ID NO: 126) CC (SEQ ID NO: 127)(SEQ ID NO: 128) hCV2346958 rs157578 C/G GGCAAGAATAGTGCCTGGCAAGAATAGTGCCTCG TGGCCCCAGCTGATCTCA CC (SEQ ID NO: 129)(SEQ ID NO: 130) (SEQ ID NO: 131) hCV25603190 rs11568506 A/GTGGTGCTTTTAGAAGTG TGGTGCTTTTAGAAGTGA CTCCATCTTTGTCCATGCCCA rs41542912ATACTTTT (SEQ ID TACTTTC (SEQ ID AATA (SEQ ID NO: 134) NO:132) NO: 133)hCV26479272 rs4594848 A/C GATGAGACAGCTTCTT TGAGACAGCTTCTTGTTTAGCCCCCTGTGAAATCACCATA GTTTAACTA (SEQ ID ACTC (SEQ ID NO: 136)TTA (SEQ ID NO: 137) NO:135) hCV28028637 rs4143832 G/T CAGAACAGGGGCATTACAGAACAGGGGCATTACT AGCTTTTGCCAGGGTGTTTG CTTG (SEQ ID NO: 138)TT (SEQ ID NO: 139) (SEQ ID NO: 140) hCV29134417 rs6884762 C/TGTCTTTGTAATTAACAA GTCTTTGTAATTAACAAGT CAAGCAAGATCTGTCAGTGGAGTATCTTAGGAG (SEQ ATCTTAGGAA (SEQ ID TACT (SEQ ID NO: 143) ID NO: 141)NO: 142) hCV29575948 rs10069772 A/G CAGAGCAAACCTAAGA CAGAGCAAACCTAAGACAGCCAAACAAGCCAGTAAATAG CACA (SEQ ID NO: 144) CG (SEQ ID NO: 145)AATCAGT (SEQ ID NO: 146) hCV31237680 rs12186803 A/G TGACACTTGGCATGTTTTGACACTTGGCATGTTTA CACAGTTGCTGAGCTGTCAAG ACTT (SEQ ID NO: 147)CTC (SEQ ID NO: 148) ATAT (SEQ ID NO: 149) hCV50000065 rs1800925 C/TTCTGGAGGACTTCTAG TCTGGAGGACTTCTAGGA TTCCCTTCTGCAGAATGAGT GAAAAC (SEQ IDAAAT (SEQ ID NO: 151) (SEQ ID NO: 152) NO:150) hCV559494 rs334902 C/GCATCCCAGGGAAGATG CATCCCAGGGAAGATGAA TCTCCGCAGTCAGCTTGTCTTAAG (SEQ ID NO: 153) C (SEQ ID NO: 154) A (SEQ ID NO: 155) hCV8932051rs848 C/A AGCACTAAAGCAGTGG CAGCACTAAAGCAGTGGA TGTTCTGCCCCTCTCCTGACACC (SEQ ID NO: 156) CA (SEQ ID NO: 157) (SEQ ID NO: 158) hDV70977429rs17618604 C/T GCCTCCTGGTCACCTC GCCTCCTGGTCACCTT GCTGCCATATCCCATCACTGA(SEQ ID NO: 159) (SEQ ID NO: 160) T (SEQ ID NO: 161) hDV70978086rs17622208 A/G GAACAGCCATACTTTTA ACAGCCATACTTTTAGCCGTGAGTGTGTTTAGGACCACT GCCAT (SEQ ID NO: 162) AC (SEQ ID NO: 163)TTAGTC (SEQ ID NO: 164)

TABLE 4 Linkage Disequilibrium (LD) SNPs Interrogated SNP Interrogatedrs LD SNP LD SNP rs Power Threshold r² r² hCV16176374 rs2227282hCV11740439 rs2023823 0.51 0.574147858 0.8788 hCV16176374 rs2227282hCV11818497 rs4266392 0.51 0.574147858 0.8824 hCV16176374 rs2227282hCV11818498 rs4425499 0.51 0.574147858 0.84 hCV16176374 rs2227282hCV11818499 rs2897442 0.51 0.574147858 0.8824 hCV16176374 rs2227282hCV11818501 rs11740584 0.51 0.574147858 0.84 hCV16176374 rs2227282hCV11818506 rs17690965 0.51 0.574147858 0.8645 hCV16176374 rs2227282hCV11818513 rs2227284 0.51 0.574147858 1 hCV16176374 rs2227282hCV15751509 rs2299009 0.51 0.574147858 0.8824 hCV16176374 rs2227282hCV15793498 rs2406539 0.51 0.574147858 0.9538 hCV16176374 rs2227282hCV15955623 rs2237059 0.51 0.574147858 0.5957 hCV16176374 rs2227282hCV16164369 rs2074529 0.51 0.574147858 0.8824 hCV16176374 rs2227282hCV16177653 rs2285700 0.51 0.574147858 0.84 hCV16176374 rs2227282hCV2558119 rs9784600 0.51 0.574147858 0.6046 hCV16176374 rs2227282hCV2558124 rs10036532 0.51 0.574147858 0.8336 hCV16176374 rs2227282hCV26478846 rs6864565 0.51 0.574147858 0.84 hCV16176374 rs2227282hCV26478847 rs6864396 0.51 0.574147858 0.84 hCV16176374 rs2227282hCV26478954 rs4426908 0.51 0.574147858 1 hCV16176374 rs2227282hCV27472356 rs3213639 0.51 0.574147858 0.84 hCV16176374 rs2227282hCV30117349 rs9784675 0.51 0.574147858 0.5818 hCV16176374 rs2227282hCV30585769 rs10062446 0.51 0.574147858 0.84 hCV16176374 rs2227282hCV31237596 rs3798129 0.51 0.574147858 0.5818 hCV16176374 rs2227282hCV31237618 rs11242127 0.51 0.574147858 0.8824 hCV16176374 rs2227282hCV31237619 rs4705965 0.51 0.574147858 0.8824 hCV16176374 rs2227282hCV31237737 rs11242122 0.51 0.574147858 0.9576 hCV16176374 rs2227282hCV31237741 rs11747814 0.51 0.574147858 0.9576 hCV16176374 rs2227282hCV8932022 rs1468215 0.51 0.574147858 0.84 hCV2259921 rs20541 hCV8932046rs847 0.51 0.893902117 0.9061 hCV2259921 rs20541 hCV8932051 rs848 0.510.893902117 0.955 hCV2259921 rs20541 hCV8932052 rs1295685 0.510.893902117 0.955 hCV2259921 rs20541 hCV8932053 rs1295686 0.510.893902117 1 hCV50000065 rs1800925 hCV11740472 rs2040704 0.510.783364112 0.8573 hCV50000065 rs1800925 hCV11818538 rs2706348 0.510.783364112 0.8573 hCV50000065 rs1800925 hCV11818554 rs12652920 0.510.783364112 0.8525 hCV50000065 rs1800925 hCV15756644 rs2301713 0.510.783364112 0.8519 hCV50000065 rs1800925 hCV15793510 rs2252775 0.510.783364112 0.8573 hCV50000065 rs1800925 hCV15892310 rs2246176 0.510.783364112 0.8525 hCV50000065 rs1800925 hCV15892315 rs2522403 0.510.783364112 0.8573 hCV50000065 rs1800925 hCV16098376 rs2106984 0.510.783364112 0.8573 hCV50000065 rs1800925 hCV16154343 rs2897443 0.510.783364112 0.8573 hCV50000065 rs1800925 hCV16164126 rs2074369 0.510.783364112 0.8519 hCV50000065 rs1800925 hCV16274080 rs2706347 0.510.783364112 0.8567 hCV50000065 rs1800925 hCV16274083 rs2244012 0.510.783364112 0.8573 hCV50000065 rs1800925 hCV16274086 rs2706338 0.510.783364112 0.8573 hCV50000065 rs1800925 hCV16274088 rs2706372 0.510.783364112 0.8479 hCV50000065 rs1800925 hCV16274090 rs2706370 0.510.783364112 0.8046 hCV50000065 rs1800925 hCV25471631 rs2522394 0.510.783364112 0.8573 hCV50000065 rs1800925 hCV2549970 rs10463893 0.510.783364112 0.8525 hCV50000065 rs1800925 hCV2549979 rs12653750 0.510.783364112 0.8573 hCV50000065 rs1800925 hCV2549980 rs2040703 0.510.783364112 0.8567 hCV50000065 rs1800925 hCV2549981 rs2240032 0.510.783364112 0.8474 hCV50000065 rs1800925 hCV2549985 rs2299015 0.510.783364112 0.8292 hCV50000065 rs1800925 hCV25812184 rs3798134 0.510.783364112 0.8525 hCV50000065 rs1800925 hCV27452177 rs3091307 0.510.783364112 0.8573 hCV50000065 rs1800925 hCV27484753 rs3798135 0.510.783364112 0.8573 hCV50000065 rs1800925 hCV29134412 rs7737470 0.510.783364112 0.8573 hCV50000065 rs1800925 hCV29134413 rs7449456 0.510.783364112 0.8418 hCV50000065 rs1800925 hCV29134415 rs6596086 0.510.783364112 0.8573 hCV50000065 rs1800925 hCV30081308 rs6871536 0.510.783364112 0.8573 hCV50000065 rs1800925 hCV30171484 rs10520114 0.510.783364112 0.8573 hCV50000065 rs1800925 hCV31237845 rs6596087 0.510.783364112 0.8525 hCV50000065 rs1800925 hDV70911845 rs17166050 0.510.783364112 0.8573 hCV8932051 rs848 hCV2259921 rs20541 0.51 0.852929420.955 hCV8932051 rs848 hCV8932046 rs847 0.51 0.85292942 0.9537hCV8932051 rs848 hCV8932052 rs1295685 0.51 0.85292942 1 hCV8932051 rs848hCV8932053 rs1295686 0.51 0.85292942 0.955

TABLE 5 Association of IL13 SNPs with psoriasis Marker Sample GenotypesAllelic Genotypic (Alleles & Position) Set Status 11 12 22 MAF HWE OR(95% CI) P P rs1800925 1 case 338 112 11 0.145 0.577 (T132020708C)control 303 139 14 0.183 0.756 0.76 (0.59-0.97) 0.0320 0.0781 2 case 335150 9 0.170 0.111 control 316 158 21 0.202 0.782 0.75 (0.60-0.94) 0.01620.0297 3 case 345 119 16 0.157 0.166 control 272 131 21 0.204 0.373 0.73(0.57-0.93) 0.0050 0.0205 Combined 0.76 (0.67-0.88) 2.50E−04 0.0029rs20541 1 case 326 131 6 0.154 0.106 (T132023863C) control 298 140 200.197 0.462 0.75 (0.59-0.95) 0.0198 0.0092 2 case 339 143 12 0.169 0.630control 312 170 12 0.196 0.047 0.83 (0.66-1.05) 0.0650 0.0907 3 case 341131 8 0.153 0.376 control 272 138 12 0.192 0.347 0.76 (0.60-0.97) 0.01660.0416 Combined 0.78 (0.68-0.90) 0.0013 0.0022 rs848 1 case 323 132 60.156 0.076 (T132024399G) control 294 145 19 0.200 0.884 0.74(0.58-0.94) 0.0148 0.0113 2 case 338 144 12 0.170 0.527 control 308 17113 0.200 0.067 0.82 (0.65-1.03) 0.0463 0.0784 3 case 334 138 8 0.1600.175 control 269 141 13 0.197 0.358 0.78 (0.61-0.99) 0.0210 0.0503Combined 0.78 (0.68-0.89) 0.0017 0.0027

TABLE 6 Three-marker IL13 haplotypes (the order of SNPs isrs1800925-rs20541-rs848) Sample Set 1 Sample Set 2 467 cases/460controls 498 cases/498controls Global P = 0.093 Global P = 0.151 No.(Frequency) in No. (Frequency) in Haplotype Case Control P OR CaseControl P OR CCG 723(0.777)  677(0.736)  0.0288 1.26 749(0.758) 710(0.717)  0.0177 1.24 TTT 74(0.079) 108(0.117)  0.0063 0.65 97(0.098)115(0.116)  0.0653 0.83 TCG 61(0.066) 61(0.066) 0.9284 0.99 70(0.071)83(0.084) 0.1503 0.83 CTT 69(0.074) 72(0.079) 0.6234 0.94 69(0.07) 80(0.081) 0.2072 0.85 Other  3(0.003)  3(0.003) NC NC  3(0.003) 2(0.002) NC NC Sample Set 3 481 cases/424controls Global P = 0.025Combined No. (Frequency) in Global P_(comb) = 0.014 Haplotype CaseControl P OR P_(comb) OR_(MH) CCG 739(0.77)  606(0.714)  0.0037 1.341.88E−04 1.27 TTT 84(0.087) 96(0.113) 0.0213 0.75 7.05E−04 0.74 TCG66(0.069) 72(0.085) 0.0999 0.80 0.201 0.86 CTT 62(0.065) 66(0.078)0.1545 0.82 0.251 0.87 Other  9(0.01) 8(0.01) NC NC NC NC

TABLE 7 HLA-cytokine pathway psoriasis relative risk estimates HLA-CIL12B/IL23R/IL13^(†) P(MLG) P(Psoriasis | MLG) RR RR (95% CI) SRR *0602carriers Very High Risk 0.0296 0.1149 3.8286 (2.359-7.277) 11.3411 *0602carriers High Risk 0.0733 0.0789 2.6294 (1.874-3.839) 7.7890 *0602carriers Moderate Risk 0.0534 0.0539 1.7971 (1.150-2.922) 5.3235 *0602carriers Low Risk 0.0121 0.0368 1.2266 (0.377-4.784) 3.6334 noncarriersVery High Risk 0.1417 0.0336 1.1195 (0.827-1.511) 3.3162 noncarriersHigh Risk 0.3608 0.0224 0.7474 (0.617-0.897) 2.2139 noncarriers ModerateRisk 0.2677 0.0150 0.5011 (0.378-0.650) 1.4843 noncarriers Low Risk0.0615 0.0101 0.3376 (0.140-0.649) 1.0000 Cytokine Pathway IL12BDiplotypes IL23R Diplotypes IL13 Genotypes Risk Category(rs6887695-rs3212227) (rs7530511-rs11209026) (rs1800925) Very High RiskAG/AG CG/CG CC High Risk AG/AG CG/CG Other High Risk AG/AG Other CC HighRisk Other CG/CG CC Moderate Risk AG/AG Other Other Moderate Risk OtherCG/CG Other Moderate Risk Other Other CC Low Risk Other Other Other^(†)Definition of IL12B/IL23R/IL13 Risk Groups

TABLE 8 Table 1 of Example Two. Association analysis of two independentSNPs in the three sample sets combined Allele/ Cases Controls SNP IDGene Genotype N (%) N (%) OR (95% CI) P rs11568506 SLC22A4 A 50 (0.017)69 (0.025) 0.68 (0.47-0.99) 0.043 G 2820 (0.983) 2677 (0.975) 1.00(reference) AA 2 (0.0014) 0 (0) NC* 0.022 AG 46 (0.032) 69 (0.050) 0.63(0.43-0.92) GG 1387 (0.0967) 1304 (0.950) 1.00 (reference) rs1800925IL13 T 453 (0.158) 540 (0.196) 0.77 (0.67-0.88) 0.00015 C 2417 (0.842)2210 (0.804) 1.00 (reference) TT 36 (0.025) 56 (0.041) 0.56 (0.37-0.86)0.00081 TC 381 (0.266) 428 (0.311) 0.78 (0.66-0.92) CC 1018 (0.709) 891(0.648) 1.00 (reference) *not calculated See supplementary Table 2 forother significant markers

TABLE 9 Table 2. Conditional association tests for 5q31 markers:P-values for marker 1 conditional on marker 2 Marker 1 rs11568506rs4143832 rs2897443 rs6884762 rs1800925 rs20541 rs848 Marker 2rs11568506 0.0138 0.0012 0.0023 0.0002 0.0012 0.0012 rs4143832 0.00220.2503 0.0067 0.0046 0.0591 0.0353 rs2897443 0.0071 0.9922 0.0736 0.04230.1103 0.1386 rs6884762 0.0114 0.0915 0.0740 0.0118 0.0129 0.0099rs1800925 0.0105 0.2493 0.2168 0.0648 0.1538 0.1006 rs20541 0.01950.8541 0.2509 0.0432 0.1123 0.8374 rs848 0.0197 0.6773 0.3075 0.03610.0676 0.7771 rs2243211 0.0145 0.5871 0.2605 0.0553 0.0330 0.0578 0.1443rs762534 0.0202 0.3471 0.2286 0.0302 0.0378 0.0822 0.0742 rs22272820.1132 0.6841 0.1164 0.0588 0.0563 0.1368 0.1943 rs12186803 0.19770.4103 0.0326 0.0005 0.0151 0.0153 0.0342 rs10069772 0.0281 0.18770.0327 0.0691 0.0054 0.0642 0.0556 Marker 1 rs2243211 rs762534 rs2227282rs12186803 rs10069772 Marker 2 rs11568506 0.0023 0.0094 0.0093 0.37540.0390 rs4143832 0.0791 0.1072 0.0531 0.3720 0.0873 rs2897443 0.18070.4214 0.0552 0.2559 0.1870 rs6884762 0.0648 0.0608 0.0148 0.0239 0.2777rs1800925 0.1136 0.3292 0.0888 0.4419 0.1153 rs20541 0.1031 0.40350.1524 0.3309 0.5399 rs848 0.2661 0.3943 0.2287 0.5391 0.5746 rs22432110.2897 0.0048 0.0992 0.1132 rs762534 0.0999 0.0034 0.0879 0.0365rs2227282 0.0238 0.0276 0.8115 0.8433 rs12186803 0.0040 0.0079 0.05570.0116 rs10069772 0.0372 0.0167 0.0878 0.0289 Note: P < 0.05 in boldface

TABLE 10 Table 3. Haplotype association tests Haplotype^(a) (rs11568506/Case Count Control Count Sample set rs1800925) (Freq.) (Freq.)P_(haplotype) Global P OR SS1 GC 771 (0.844) 713 (0.787) 0.0019 0.00281.46 GT 131 (0.143) 167 (0.184) 0.018 0.74 AC 12 (0.013) 26 (0.029)0.019 0.45 SS2 GC 796 (0.807) 765 (0.781) 0.13 0.11 1.18 GT 168 (0.170)199 (0.203) 0.052 0.81 AC 22 (0.022) 15 (0.015) 0.36 1.48 SS3 GC 799(0.830) 651 (0.764) 9.11E-04 0.0028 1.51 GT 147 (0.153) 175 (0.205)6.87E-03 0.70 AC 13 (0.014) 26 (0.031) 0.031 0.45 All^(b) GC 2366(0.827) 2128 (0.777) 5.67E-06 8.93E−05 1.37 GT 446 (0.156) 542 (0.198)6.01E-05 0.75 AC 47 (0.017) 68 (0.025) 0.053 0.66 ^(a)Frequency of AThaplotype is <0.001 in both cases or controls. ^(b)Because haplotypecounts were estimated, these counts may vary slightly from the sum ofthe three individudal sample sets.

TABLE 11 Table 4. Association of putative CD SNPs with psoriasisPsoriasis (SS1+SS2+SS3) CD (WTCCC)^(a) Case Control Case Control alleleallele allele allele Position fre- fre- fre- fre- Marker Chr (bp) Genequency quency P_(allelic) OR (95% CI) quency quency P_(allelic) OR (95%CI) rs6596075 5 131,770,127 0.162 0.164 0.82 0.98 (0.85-1.14) 0.1270.166 5.40E−07 0.73 (0.65-0.83) rs2285673 5 131,783,868 LOC441108 0.2260.235 0.43 0.95 (0.84-1.08) 0.212 0.252 1.50E−05 0.80 (0.73-0.89)rs4540166 5 131,807,756 LOC441108 0.205 0.212 0.52 0.96 (0.84-1.09)0.189 0.228 8.98E−06 0.79 (0.71-0.88) rs10077785 5 131,829,057 0.2090.218 0.45 0.95 (0.84-1.09) 0.192 0.234 1.81E−06 0.78 (0.70-0.86)rs2522057 5 131,829,846 0.444 0.414 0.022 1.13 (1.02-1.26) 0.478 0.4221.01E−07 1.29 (1.20-1.33) ^(a)Data are from WTCCC (3).

TABLE 12 Association results in sample set 1. Case^(b) Control^(b) RSNumber Gene Position and alleles^(a) 11 12 22 HWE^(c) 11 12 22 HWE^(c)P_(allelic) P_(genotypic) rs12656759 C131395509T 98 237 126 0.51 99 240120 0.35 0.75 0.92 rs2073506 T131422637C 4 63 394 0.33 2 71 386 0.760.71 0.55 rs31481 IL3 A131425101G 13 107 339 0.19 12 120 325 0.86 0.450.59 rs11575022 C131429914A 2 43 416 0.33 7 42 410 0.0006 0.35 0.23rs2069626 CSF2 G131438678A 0 15 446 1 0 9 450 1 0.22 rs743564 CSF2C131438778T 76 228 155 0.63 72 222 165 0.92 0.51 0.78 rs25882 CSF2C131439359T 18 142 298 0.88 19 150 290 1 0.57 0.84 rs25887 C131443960A83 232 146 0.64 87 223 149 0.85 0.96 0.86 rs25888 A131444345G 0 25 436 10 21 438 1 0.56 rs31467 C131464737T 106 233 122 0.85 116 227 116 0.850.46 0.71 rs39897 C131464795T 96 235 130 0.64 93 239 127 0.35 0.96 0.95rs154735 A131465431G 2 56 402 1 1 56 402 1 0.86 0.86 rs247008A131475003G 42 198 221 0.91 41 213 205 0.20 0.47 0.56 rs156055A131528076G 4 65 390 0.51 3 64 391 0.74 0.80 0.93 rs156033 T131555220C12 126 323 1 11 131 317 0.74 0.82 0.91 rs2278398 P4HA2 G131558340A 100244 117 0.23 97 229 132 0.93 0.40 0.49 rs156030 P4HA2 A131558816G 0 49411 0.63 2 33 424 0.16 0.19 rs152050 T131564725C 52 215 193 0.54 54 217186 0.48 0.69 0.92 rs10520127 P4HA2 T131567154C 2 64 394 1 3 68 387 10.58 0.83 rs17618604 P4HA2 T131570083C 9 84 368 0.15 2 112 345 0.02 0.300.01 rs283763 P4HA2 T131581144A 14 159 288 0.19 16 162 281 0.26 0.650.89 rs7733814 P4HA2 T131584208C 2 59 400 1 1 55 401 1 0.60 0.81rs157578 P4HA2 C131589221G 3 102 356 0.18 12 108 339 0.34 0.09 0.04rs10036208 T131599222C 48 206 207 0.83 62 186 211 0.05 0.64 0.24rs11749843 A131600397G 0 8 452 1 0 5 454 1 0.41 rs2405271 C131601292G 11151 299 0.13 19 138 302 0.55 0.82 0.26 rs334902 C131614458G 78 244 1390.11 101 207 151 0.06 0.61 0.04 rs4594848 A131614497C 94 247 120 0.13107 208 143 0.07 0.63 0.05 rs7727038 C131618156T 86 226 149 1 98 214 1470.22 0.52 0.57 rs162881 PDLIM4 G131636693T 4 73 383 0.77 5 85 369 1 0.260.54 rs162896 T131640775C 0 33 427 1 0 20 439 1 0.07 rs7737937A131642880G 10 125 325 0.73 8 118 333 0.71 0.49 0.77 rs162899G131643492A 26 175 260 0.71 25 178 254 0.45 0.87 0.95 rs272895G131644273A 6 114 341 0.43 6 101 352 0.83 0.39 0.63 rs381870 T131650200A11 146 304 0.21 18 142 299 0.77 0.52 0.41 rs162892 A131651149G 47 210203 0.53 48 194 216 0.67 0.53 0.59 rs162889 T131652285C 18 191 252 0.0222 177 260 0.31 0.78 0.59 rs2662314 T131653068C 7 115 338 0.56 7 107 3440.84 0.61 0.85 rs157572 C131654011G 39 204 218 0.44 38 187 234 0.91 0.360.52 rs3792876 SLC22A4 T131665208C 4 62 394 0.32 3 60 396 0.72 0.73 0.92rs3792884 SLC22A4 G131679160A 5 90 361 1 3 90 361 0.45 0.79 0.78rs11739484 SLC22A4 G131684659A 0 25 436 1 0 23 436 1 0.78 rs273912SLC22A4 G131689248T 37 186 238 0.91 50 179 230 0.10 0.30 0.33 rs272879SLC22A4 C131698445G 61 211 189 0.84 69 209 181 0.49 0.45 0.72 rs11568506SLC22A4 A131699359G 0 12 449 1 0 27 430 1 0.01 rs17622208 SLC22A5A131744949G 97 252 112 0.05 114 208 137 0.05 0.71 0.02 rs7731390 SLC22A5G131749648C 0 47 413 0.62 1 38 420 0.59 0.45 rs17689550 SLC22A5T131750964C 5 86 370 1 6 96 356 1 0.35 0.64 rs35306350 SLC22A5T131751187C 81 253 125 0.02 102 213 143 0.19 0.89 0.03 rs274549 SLC22A5A131757017C 13 140 307 0.64 7 135 317 0.09 0.30 0.36 rs11739135C131761296G 79 214 167 0.50 79 216 161 0.70 0.80 0.95 rs6596075G131770127C 13 140 307 0.64 7 135 317 0.09 0.30 0.36 rs4705943 LOC441108G131782903A 6 87 368 0.63 7 80 372 0.30 0.73 0.83 rs4705944 LOC441108A131783163T 1 31 429 0.45 3 26 430 0.01 0.91 0.50 rs2285673 LOC441108T131783868C 25 183 252 0.32 25 178 255 0.45 0.83 0.96 rs1004234LOC441108 A131785000G 2 56 401 1 0 54 405 0.39 0.56 rs11958162 LOC441108A131799815T 8 105 348 1 3 107 349 0.13 0.60 0.31 rs4540166 LOC441108T131807756C 19 164 277 0.50 22 158 279 1 0.96 0.85 rs7713818 LOC441108T131816650C 45 201 213 0.91 46 216 197 0.25 0.40 0.56 rs10477741LOC441108 G131823209T 7 94 358 0.82 5 95 359 0.82 0.83 0.85 rs6894249LOC441108 G131825446A 64 231 166 0.28 59 230 169 0.20 0.68 0.89rs2522051 LOC441108 C131825477T 81 241 136 0.16 108 208 143 0.06 0.350.04 rs10077785 T131829057C 20 164 277 0.59 19 163 277 0.50 0.90 0.99rs2522057 G131829846C 79 237 145 0.34 79 222 157 1 0.56 0.62 rs2522064A131834387G 10 147 304 0.12 20 148 290 0.89 0.19 0.16 rs17715481G131843283A 1 67 393 0.50 0 77 382 0.06 0.47 rs10072700 C131844802A 37174 249 0.41 29 174 256 1 0.41 0.59 rs2070721 IRF1 G131853741T 98 219144 0.40 90 227 141 1 0.80 0.78 rs2548997 G131863294A 58 195 207 0.25 47208 203 0.60 0.70 0.45 rs4143832 T131890876G 12 102 345 0.17 17 126 3160.33 0.03 0.10 rs4705959 C131893690T 26 179 253 0.54 32 159 268 0.210.65 0.33 rs2706399 A131895601G 104 232 124 0.85 103 242 107 0.16 0.460.50 rs739719 A131900764C 6 72 383 0.25 2 71 385 0.76 0.48 0.36rs2069822 IL5 C131906781T 0 19 441 1 1 15 442 0.14 0.75 rs2069812A131907815G 40 216 205 0.13 43 194 220 1 0.50 0.41 rs2897443 RAD50T131957493G 11 111 338 0.57 14 137 308 0.88 0.04 0.11 rs6884762 RAD50T131966629C 0 15 446 1 0 34 424 1 0.01 rs17772583 RAD50 G131981409A 27180 253 0.54 30 163 266 0.45 0.57 0.52 rs2237060 RAD50 G131998784T 93234 134 0.64 87 222 150 0.78 0.30 0.49 rs2158177 RAD50 G132011957A 8 112339 0.85 12 133 314 0.74 0.06 0.17 rs1800925 T132020708C 11 112 338 0.5814 139 303 0.76 0.03 0.08 rs20541 IL13 A132023863G 6 131 326 0.11 20 140298 0.46 0.02 0.01 rs848 IL13 A132024399C 6 132 323 0.08 19 145 294 0.880.01 0.01 rs1295683 A132026775G 3 78 380 1 6 70 383 0.24 0.89 0.49rs2243297 A132027070T 0 26 435 1 2 34 423 0.18 0.12 rs2243211A132029321C 0 54 406 0.39 5 72 379 0.39 0.01 rs762534 A132032655C 0 47414 0.62 3 69 387 1 0.01 rs2243248 G132036543T 3 50 408 0.23 1 71 3870.34 0.11 0.08 rs2227282 IL4 C132041078G 18 173 270 0.15 45 162 251 0.020.02 0.00 rs2243263 IL4 C132041198G 3 84 373 0.60 9 90 360 0.26 0.170.17 rs12186803 KIF3A A132067968G 4 103 353 0.38 15 110 333 0.15 0.040.02 rs10069772 KIF3A A132068587G 4 90 362 0.81 11 105 343 0.43 0.040.08 rs17691077 KIF3A C132071250A 9 102 349 0.68 7 97 355 0.83 0.54 0.81^(a)Positions according to genomic contig NT_034772.5 (EntrezNucleotide). The minor allele is listed first, followed by the positionin National Center for Biotechnology Information Genome Build 36.2 andthen the major allele. ^(b)Counts of genotype 11, 12 and 22. ^(c)P-valuefrom Hardy-Weinberg Equilibrium test ^(d) The data for these three SNPswas reported previously (21).

TABLE 13 Minor allele frequencies and allele-based association of 5q31SNPs with psoriasis Position and ^(b)Case ^(b)Control RS Number Publicalleles^(a) Study 11 12 22 Sum MAF HWE 11 12 22 rs11568506 SLC22A4A131699359G SS1 0 12 449 461 0.013 1 0 27 430 SS2 2 18 473 493 0.0220.02 0 16 474 SS3 0 16 465 481 0.017 1 0 26 400 All 2 46 1387 1435 0.0170 69 1304 rs4143832 LOC441108 T131890876G SS1 12 102 345 459 0.137 0.1717 126 316 SS2 11 151 331 493 0.175 0.22 21 153 318 SS3 15 129 337 4810.165 0.51 15 117 294 All 38 382 1013 1433 0.160 53 396 928 rs2897443RAD50 T131957493G SS1 11 111 338 460 0.145 0.57 14 137 308 SS2 9 161 323493 0.182 0.03 22 154 316 SS3 14 124 344 482 0.158 0.49 22 130 273 All34 396 1005 1435 0.162 58 421 897 rs6884762 RAD50 T131966629C SS1 0 15446 461 0.016 1 0 34 424 SS2 0 30 463 493 0.030 1 0 30 462 SS3 0 16 466482 0.017 1 0 31 394 All 0 61 1375 1436 0.021 0 95 1280 rs1800925 IL13T132020708C SS1 11 112 338 461 0.145 0.58 14 139 303 SS2 9 150 335 4940.170 0.11 21 158 316 SS3 16 119 345 480 0.157 0.17 21 131 272 All 36381 1018 1435 0.158 56 428 891 rs20541 IL13 A132023863G SS1 6 131 326463 0.154 0.11 20 140 298 SS2 12 143 339 494 0.169 0.63 12 170 312 SS3 8131 341 480 0.153 0.38 12 138 272 All 26 405 1006 1437 0.159 44 448 882rs848 IL13 A132024399C SS1 6 132 323 461 0.156 0.076 19 145 294 SS2 12144 338 494 0.170 0.53 13 171 308 SS3 8 138 334 480 0.160 0.18 13 141269 All 26 414 995 1435 0.162 45 457 871 rs2243211 A132029321C SS1 0 54406 460 0.059 0.39 5 72 379 SS2 0 51 441 492 0.052 0.63 3 67 420 SS3 164 416 481 0.069 0.72 2 61 362 All 1 169 1263 1433 0.060 10 200 1161rs762534 A132032655C SS1 0 47 414 461 0.051 0.62 3 69 387 SS2 1 54 437492 0.057 1 4 67 420 SS3 1 48 433 482 0.052 1 1 48 376 All 2 149 12841435 0.053 8 184 1183 rs2227282 IL4 C132041078G SS1 18 173 270 461 0.2270.15 45 162 251 SS2 27 188 279 494 0.245 0.63 34 193 265 SS3 31 143 306480 0.214 0.01 31 172 223 All 76 504 855 1435 0.229 110 527 739rs12186803 KIF3A A132067968G SS1 4 103 353 460 0.121 0.38 15 110 333 SS210 111 373 494 0.133 0.56 7 111 374 SS3 7 86 389 482 0.104 0.33 12 94320 All 21 300 1115 1436 0.119 34 315 1027 rs10069772 KIF3A A132068587GSS1 4 90 362 456 0.107 0.81 11 105 343 SS2 10 99 381 490 0.121 0.29 11120 359 SS3 5 101 372 478 0.116 0.66 6 101 317 All 19 290 1115 14240.115 28 326 1019 Position and ^(b)Control RS Number Public alleles^(a)Study Sum MAF HWE P^(c) OR (95% CI) rs11568506 SLC22A4 A131699359G SS1457 0.030 1 0.014 0.43 (0.21-0.86) SS2 490 0.016 1 0.34 1.37 (0.71-2.63)SS3 426 0.031 1 0.050 0.53 (0.28-1.00) All 1373 0.025 0.043 0.68(0.47-0.99) rs4143832 LOC441108 T131890876G SS1 459 0.174 0.33 0.0290.75 (0.58-0.97) SS2 492 0.198 0.67 0.20 0.86 (0.68-1.08) SS3 426 0.1730.40 0.68 0.94 (0.74-1.21) All 1377 0.182 0.026 0.85 (0.74-0.98)rs2897443 RAD50 T131957493G SS1 459 0.180 0.88 0.041 0.77 (0.60-0.98)SS2 492 0.201 0.57 0.27 0.88 (0.70-1.10) SS3 425 0.205 0.23 0.0092 0.72(0.57-0.92) All 1376 0.195 0.0010 0.78 (0.69-0.91) rs6884762 RAD50T131966629C SS1 458 0.037 1 0.0055 0.42 (0.23-0.79) SS2 492 0.030 1 0.960.99 (0.59-1.66) SS3 425 0.036 1 0.0078 0.44 (0.24-0.82) All 1375 0.0350.0025 0.61 (0.44-0.84) rs1800925 IL13 T132020708C SS1 456 0.183 0.760.029 0.76 (0.59-0.97) SS2 495 0.202 0.78 0.068 0.81 (0.64-1.02) SS3 4240.204 0.37 0.010 0.73 (0.57-0.93) All 1375 0.196 0.00015 0.77(0.67-0.88) rs20541 IL13 A132023863G SS1 458 0.197 0.46 0.018 0.75(0.59-0.95) SS2 494 0.196 0.047 0.12 0.83 (0.66-1.05) SS3 422 0.192 0.350.029 0.76 (0.60-0.97) All 1374 0.195 0.00043 0.78 (0.68-0.90) rs848IL13 A132024399C SS1 458 0.200 0.88 0.015 0.74 (0.58-0.94) SS2 492 0.2000.067 0.085 0.82 (0.65-1.03) SS3 423 0.197 0.36 0.040 0.78 (0.61-0.99)All 1373 0.199 0.00035 0.78 (0.68-0.89) rs2243211 A132029321C SS1 4560.090 0.39 0.011 0.63 (0.44-0.90) SS2 490 0.074 0.74 0.039 0.67(0.46-0.98) SS3 425 0.076 1 0.52 0.88 (0.62-1.26) All 1371 0.080 0.00240.72 (0.58-0.89) rs762534 A132032655C SS1 459 0.082 1 0.0081 0.60(0.41-0.87) SS2 491 0.076 0.51 0.084 0.72 (0.51-1.04) SS3 425 0.059 10.52 0.87 (0.58-1.31) All 1375 0.073 0.0031 0.72 (0.58-0.89) rs2227282IL4 C132041078G SS1 458 0.275 0.02 0.017 0.77 (0.62-0.95) SS2 492 0.2651 0.30 0.89 (0.73-1.10) SS3 426 0.275 0.90 0.0024 0.71 (0.57-0.88) All1376 0.271 0.00022 0.79 (0.70-0.89) rs12186803 KIF3A A132067968G SS1 4580.153 0.15 0.045 0.76 (0.58-0.99) SS2 492 0.127 0.84 0.71 1.05(0.80-1.36) SS3 426 0.138 0.15 0.023 0.71 (0.54-0.95) All 1376 0.1390.027 0.83 (0.71-0.98) rs10069772 KIF3A A132068587G SS1 459 0.138 0.430.044 0.74 (0.56-0.99) SS2 490 0.145 0.72 0.13 0.81 (0.62-1.05) SS3 4240.133 0.67 0.27 0.85 (0.64-1.13) All 1373 0.139 0.0074 0.80 (0.68-0.94)^(a)Positions according to genomic contig NT_034772.5 (EntrezNucleotide). The minor allele is listed first, followed by the positionin National Center for Biotechnology Information Genome Build 36.2 andthen the major allele. ^(b)Counts for genotypes 11, 12 and 22; MAF:minor allele frequency: HWE: Hardy-Weinberg P-value ^(c)P values and ORsare calculated by chi-square method for SS1, SS2 and SS3 and byMantel-Haenszel method for the three sample sets combined (All);P-values for the three IL13 markers in the combined sample sets areslightly different from our previous report which used Fisher's exacttest (21).

TABLE 14 LD measures of the twelve significant markers in controls ofsample set 1. D′ rs11568506 rs4143832 rs2897443 rs6884762 rs1800925rs20541 rs848 r² rs11568506 0.394 0.467 0.04 0.953 0.996 0.997 rs41438320.001 0.721 0.918 0.747 0.296 0.3 rs2897443 0.001 0.501 1 0.908 0.5250.524 rs6884762 0.001 0.154 0.177 1 0.56 0.556 rs1800925 0.006 0.5170.801 0.174 0.552 0.55 rs20541 0.007 0.075 0.245 0.05 0.278 0.993 rs8480.008 0.076 0.241 0.048 0.273 0.979 rs2243211 0.003 0.067 0.177 0.1210.263 0.318 0.328 rs762534 0.003 0.091 0.169 0.133 0.212 0.245 0.244rs2227282 0.01 0.067 0.066 0.031 0.059 0.12 0.128 rs12186803 0.027 0.0490.044 0.007 0.035 0.057 0.065 rs10069772 0.005 0.007 0.011 0.061 0.0160.046 0.047 D′ rs2243211 rs762534 rs2227282 rs12186803 rs10069772 r²rs11568506 1 1 0.349 0.408 0.993 rs4143832 0.378 0.465 0.349 0.24 0.097rs2897443 0.628 0.646 0.34 0.231 0.123 rs6884762 0.549 0.555 0.557 0.9870.505 rs1800925 0.778 0.735 0.316 0.21 0.148 rs20541 0.895 0.825 0.4310.279 0.265 rs848 0.913 0.826 0.441 0.3 0.271 rs2243211 0.805 0.1750.855 0.344 rs762534 0.588 0.26 1 0.415 rs2227282 0.008 0.016 0.9560.849 rs12186803 0.013 0.016 0.436 0.999 rs10069772 0.074 0.096 0.3050.029

TABLE 15 Chromosome 5q31 markers in high LD with rs1800925 markerPosition (bp) Gene Symbol SNPType r² with 1800925 rs12652920 131,913,139IL5 putative TFBS^(a) 0.895 rs2706338 131,923,748 RAD50 Intron 0.897rs2244012 131,929,124 LOC441108 Intron 0.897 rs2299015 131,929,396 RAD50Intron 0.877 rs2706347 131,933,016 RAD50 putative TFBS^(a) 0.897rs2706348 131,933,709 RAD50 Intron 0.897 rs17166050 131,943,112 RAD50putative TFBS^(a) 0.897 rs2522403 131,943,216 RAD50 Intron 0.897rs2246176 131,945,249 RAD50 Intron 0.895 rs2252775 131,946,343 RAD50Intron 0.897 rs10463893 131,955,938 RAD50 Intron 0.895 rs2897443131,957,493 RAD50 putative TFBS^(a) 0.897 rs2706370 131,960,915 RAD50Intron 0.829 rs2706372 131,963,376 RAD50 Intron 0.89 rs12187537131,967,803 RAD50 Intron 0.817 rs2522394 131,972,028 RAD50 Intron 0.897rs10520114 131,976,790 RAD50 Intron 0.897 rs2301713 131,979,895 RAD50Intron 0.892 rs6596086 131,980,121 RAD50 Intron 0.897 rs2106984131,980,965 RAD50 Intron 0.897 rs7449456 131,981,326 RAD50 Intron 0.89rs3798135 131,993,008 RAD50 Intron 0.897 rs3798134 131,993,078 RAD50Intron 0.894 rs6596087 131,996,508 RAD50 Intron 0.881 rs6871536131,997,773 RAD50 Intron 0.897 rs12653750 131,999,801 RAD50 Intron 0.897rs2040703 132,000,157 RAD50 Intron 0.897 rs2040704 132,001,076 RAD50putative TFBS^(a) 0.897 rs2074369 132,001,562 RAD50 Intron 0.892rs7737470 132,001,962 RAD50 Intron 0.897 rs2240032 132,005,026 RAD50Intron 0.892 rs3091307 132,017,035 Intron 0.897 putative TFBS*(transcription factor binding site)

TABLE 16 Pairwise genotype counts for cases and controls. rs11568506rs1800925 Cases N Controls N GG CC 978 831 GG CT 370 414 AG CC 38 52 GGTT 35 56 AG CT 7 16 AA CC 2 AG TT 1

What is claimed is:
 1. A method for reducing the risk of psoriasis in ahuman, the method comprising: a) testing nucleic acid from said humanfor a polymorphism in gene IL13 as represented by position 101 of SEQ IDNO:22 or its complement by contacting said nucleic acid with anoligonucleotide that specifically hybridizes to C at said position 101of SEQ ID NO:22 or G at said complement; b) detecting said C or said G;c) identifying said human as having an increased risk for psoriasis dueto the presence of said C or said G; and d) administering a therapeuticagent suitable for prevention or treatment of psoriasis to said human.2. The method of claim 1, wherein said method comprises preparing asample from said human that is enriched for a fragment of said nucleicacid that includes said position 101 of SEQ ID NO:22 or its complementby amplifying said fragment by polymerase chain reaction (PCR).
 3. Themethod of claim 1, wherein said testing comprises amplifying bypolymerase chain reaction (PCR) a fragment of said nucleic acid thatincludes said position 101 of SEQ ID NO:22 or its complement to therebycreate an amplicon containing said position, and contacting saidamplicon with said oligonucleotide.
 4. The method of claim 1, whereinthe nucleotide sequence of said oligonucleotide consists of a segment ofat least 12 contiguous nucleotides of SEQ ID NO:22 or its complementthat includes said position
 101. 5. The method of claim 1, wherein saidoligonucleotide is an allele-specific probe or an allele-specificprimer.
 6. The method of claim 1, wherein said oligonucleotide is anallele-specific primer comprising SEQ ID NO:150.
 7. The method of claim1, wherein said testing comprises allele-specific amplification, andfurther wherein said detecting comprises detecting the presence of anamplicon.
 8. The method of claim 1, wherein said oligonucleotide isdetectably labeled with a fluorescent dye.
 9. The method of claim 1,wherein said human is homozygous for said C or said G.
 10. The method ofclaim 1, wherein said human is heterozygous for said C or said G. 11.The method of claim 1, wherein said therapeutic agent comprises ananti-IL13 antibody.
 12. A method for reducing the risk of psoriasis in ahuman, the method comprising: a) receiving an identification of a humanas having an increased risk for psoriasis due to a polymorphism in geneIL13 comprising C at position 101 of SEQ ID NO:22 or G at itscomplement; and b) administering a therapeutic agent suitable forprevention or treatment of psoriasis to said human.
 13. The method ofclaim 12, wherein said human is homozygous for said C or said G.
 14. Themethod of claim 12, wherein said human is heterozygous for said C orsaid G.
 15. The method of claim 12, wherein said therapeutic agentcomprises an anti-IL13 antibody.